化工过程水分配网络合成的研究
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摘要
随着水资源和能源的日趋紧缺以及社会对环境保护的日益重视,以提高水资源和能源利用效率及废水最小化排放为目标的化工过程水分配网络和热交换网络合成问题已成为国内外过程系统工程领域研究的热点。然而由于过程系统涉及多种操作单元、过程不确定性以及可能存在多种热交换方式等因素,目前针对连续过程、间歇过程水分配网络合成以及考虑热集成的水分配网络合成的研究还不十分完善。针对存在的问题,本文进行了以下的研究工作:
1、通过引入改进的虚拟操作单元,将带有水的损失或水的生成的固定流率用水单元用两个虚拟的操作单元等价代替,建立了用于可同时处理固定流率与固定污染物负荷两类用水操作的连续过程用水网络合成问题的目标设定方法,该方法能够较迅速并准确地确定用水网络问题的最小新鲜水用量及其夹点位置,包括可能存在的多夹点问题。
2、基于浓度间隔分析技术,通过引入区域分解和水源分配的策略,建立了用水网络设计的新方法。该方法避免了网络设计因分流、混合、回路识别及断开等比较繁琐的网络设计过程。此外,作为一种启发式的设计方法,该方法还能有效解决数学规划法等求解困难的问题以及黑箱模型问题难于理解的局限。
3、基于用于连续过程用水网络的浓度间隔分析技术,通过引入时间间隔,建立了针对单批生产与多批重复生产的间歇过程用水网络合成的系统化方法——时间、浓度间隔分析技术。该方法能够有效地应用于上述用水网络合成问题,且更为快捷和方便。
4、基于求解不确定性问题的对称模糊规划方法,提出了针对单组分负荷不确定用水网络合成问题的改进的对称模糊规划模型和用水网络设计的多目标混合整数对称模糊规划模型,同时提出了求解这一多目标问题的主目标设定法策略。算例的求解结果表明,所提模型以及求解策略对负荷不确定的工业用水网络的合成问题有良好的适用性,从而获得优化流程设计。
5、针对带有等式约束的非线性规划(NLP)与混合整数非线性规划(MINLP)问题,建立了一种改进的粒子群优化(PSO)算法——简约空间粒子群算法(R-PSO)。应用多个例子对该算法的有效性进行了验证。
6、基于分散式废水处理网络的超结构,建立了废水处理网络系统最优化的非线性规划(NLP)模型和混合整数非线性规划(MINLP)模型,并采用新型随机型算法—简约空间粒子群优化(R-PSO)算法求解上述复杂非线性最优化问题。
7、通过考虑用水网络特有的直接换热,建立了用水网络与换热网络同时优化问题的“净热量”集成方法,并且结合简约空间的粒子群优化算法,建立了用于考虑能量集成的用水网络合成的演化计算方法。该方法能够充分考虑用水网络系统中存在的直接热交换,进而实现用水系统的最优能量集成并获得较好的热交换网络(所需换热面积较少);同时,作为一种基于演化的优化方法,该方法既能应用于单组分用水系统,也能适应于复杂的非线性多组分系统,且能够实现全系统(用水网络以及热交换网络)的费用最小化。
With the increasingly scarcity of water and energy resource and ever-tightening environmental regulations on industrial effluent, the research on synthesis and optimization of water network and heat exchanger network for improving the utilization efficiency of water and energy resource has been becoming more focused, and motivated than ever before. However, such as multiple category operations, uncertainty, multiple heat recoveries model etc. for the synthesis problems are so complex that the currently available methods demonstrate still some major limitations. With the consideration of the above issues, we have performed the following research.
1. A strategy for fresh water minimization is developed for continuous water utilization systems with both fixed flowrate (non-mass-transfer-based) and fixed contaiminent (mass-ransfer -based) operations.Through introducing the concept of improved ficitious operation units, the problem of water losing and/or generating for the fixed flowrate operations in continuous water utilization system can be handled easily without tedious graphical or iterative procedure, the pinch point can also be located simultaneously.
2. Based on the knowledge of concentration interval analysis technique, a heuristic-based approach is presented to generate water utilization networks.The proposed method has the advantage of capability of considering fixed flowrate operations, the necessity of identifying and breaking loops and the limitation of flow distributing or mixing can be avoided.
3. Based on the improved concentration interval analysis technique for continuous process water using system, a time-dependent concentration interval analysis (CIA) method to solve the problems of synthesis of single and repeated batch water-using systems is presented. The proposed method can effectively minimize the freshwater consumption for single or repeated batch operations and can determine a preferable storage tank capacity.
4. An improved symmetric fuzzy linear programming (SFLP)model and a multi-objective mixed-integer SFLP model are developed for fresh water minimization of single-component water utilization networks with mass load uncertainty. A main criterion limiting (MCL) solution strategy is further developed for the multi-objective problem. The solution results of the example problems demonstrate that the proposed modeling and solution procedures have a good suitability, and then provide an optimum design for the networks.
5. Aiming at the nonlinear programming problem (NLP) and the mixed-integer nonlinear programming problem (MINLP) with equality constraints, an improve particle swarm optimization (PSO) algorithm, i.e. reduced space optimization(R-PSO) algorithm is developed. The advantage of proposed algorithm in applicability and efficiency is demonstrated by several test problems.
6. Based on a superstructure representation, a nonlinear programming (NLP) model as well as a mixed-integer nonlinear programming (MINLP) model was proposed for the optimal design of distributed wastewater treatment network system. Furthermore, to overcome the solving difficulty of the corresponding non-convexity problem, a newly proposed random search based optimization method– particle swarm optimization (PSO) is introduced and applied to develop a global optimization method for the wastewater treatment network design.
7. By considering of the direct heat recovery that special existing in water using network, a net-heat integration approach for the simultaneous heat and water network integration. And combination with R-PSO algorithms, proposed an evolutionary approach to solve the simultaneous heat and water network optimization problem. By fully taking into account the possibility of the heat recoverie, the proposed approach can realize the optimum energy consumption target and heat exchange network in water using system. Furthermore, as an evolutionary-based approach, the proposed approach can deal with both single and multi-contaminant water-using systems, and can realize the economic trade-off between water network and heat exchanger network.
1、通过引入改进的虚拟操作单元,将带有水的损失或水的生成的固定流率用水单元用两个虚拟的操作单元等价代替,建立了用于可同时处理固定流率与固定污染物负荷两类用水操作的连续过程用水网络合成问题的目标设定方法,该方法能够较迅速并准确地确定用水网络问题的最小新鲜水用量及其夹点位置,包括可能存在的多夹点问题。
2、基于浓度间隔分析技术,通过引入区域分解和水源分配的策略,建立了用水网络设计的新方法。该方法避免了网络设计因分流、混合、回路识别及断开等比较繁琐的网络设计过程。此外,作为一种启发式的设计方法,该方法还能有效解决数学规划法等求解困难的问题以及黑箱模型问题难于理解的局限。
3、基于用于连续过程用水网络的浓度间隔分析技术,通过引入时间间隔,建立了针对单批生产与多批重复生产的间歇过程用水网络合成的系统化方法——时间、浓度间隔分析技术。该方法能够有效地应用于上述用水网络合成问题,且更为快捷和方便。
4、基于求解不确定性问题的对称模糊规划方法,提出了针对单组分负荷不确定用水网络合成问题的改进的对称模糊规划模型和用水网络设计的多目标混合整数对称模糊规划模型,同时提出了求解这一多目标问题的主目标设定法策略。算例的求解结果表明,所提模型以及求解策略对负荷不确定的工业用水网络的合成问题有良好的适用性,从而获得优化流程设计。
5、针对带有等式约束的非线性规划(NLP)与混合整数非线性规划(MINLP)问题,建立了一种改进的粒子群优化(PSO)算法——简约空间粒子群算法(R-PSO)。应用多个例子对该算法的有效性进行了验证。
6、基于分散式废水处理网络的超结构,建立了废水处理网络系统最优化的非线性规划(NLP)模型和混合整数非线性规划(MINLP)模型,并采用新型随机型算法—简约空间粒子群优化(R-PSO)算法求解上述复杂非线性最优化问题。
7、通过考虑用水网络特有的直接换热,建立了用水网络与换热网络同时优化问题的“净热量”集成方法,并且结合简约空间的粒子群优化算法,建立了用于考虑能量集成的用水网络合成的演化计算方法。该方法能够充分考虑用水网络系统中存在的直接热交换,进而实现用水系统的最优能量集成并获得较好的热交换网络(所需换热面积较少);同时,作为一种基于演化的优化方法,该方法既能应用于单组分用水系统,也能适应于复杂的非线性多组分系统,且能够实现全系统(用水网络以及热交换网络)的费用最小化。
With the increasingly scarcity of water and energy resource and ever-tightening environmental regulations on industrial effluent, the research on synthesis and optimization of water network and heat exchanger network for improving the utilization efficiency of water and energy resource has been becoming more focused, and motivated than ever before. However, such as multiple category operations, uncertainty, multiple heat recoveries model etc. for the synthesis problems are so complex that the currently available methods demonstrate still some major limitations. With the consideration of the above issues, we have performed the following research.
1. A strategy for fresh water minimization is developed for continuous water utilization systems with both fixed flowrate (non-mass-transfer-based) and fixed contaiminent (mass-ransfer -based) operations.Through introducing the concept of improved ficitious operation units, the problem of water losing and/or generating for the fixed flowrate operations in continuous water utilization system can be handled easily without tedious graphical or iterative procedure, the pinch point can also be located simultaneously.
2. Based on the knowledge of concentration interval analysis technique, a heuristic-based approach is presented to generate water utilization networks.The proposed method has the advantage of capability of considering fixed flowrate operations, the necessity of identifying and breaking loops and the limitation of flow distributing or mixing can be avoided.
3. Based on the improved concentration interval analysis technique for continuous process water using system, a time-dependent concentration interval analysis (CIA) method to solve the problems of synthesis of single and repeated batch water-using systems is presented. The proposed method can effectively minimize the freshwater consumption for single or repeated batch operations and can determine a preferable storage tank capacity.
4. An improved symmetric fuzzy linear programming (SFLP)model and a multi-objective mixed-integer SFLP model are developed for fresh water minimization of single-component water utilization networks with mass load uncertainty. A main criterion limiting (MCL) solution strategy is further developed for the multi-objective problem. The solution results of the example problems demonstrate that the proposed modeling and solution procedures have a good suitability, and then provide an optimum design for the networks.
5. Aiming at the nonlinear programming problem (NLP) and the mixed-integer nonlinear programming problem (MINLP) with equality constraints, an improve particle swarm optimization (PSO) algorithm, i.e. reduced space optimization(R-PSO) algorithm is developed. The advantage of proposed algorithm in applicability and efficiency is demonstrated by several test problems.
6. Based on a superstructure representation, a nonlinear programming (NLP) model as well as a mixed-integer nonlinear programming (MINLP) model was proposed for the optimal design of distributed wastewater treatment network system. Furthermore, to overcome the solving difficulty of the corresponding non-convexity problem, a newly proposed random search based optimization method– particle swarm optimization (PSO) is introduced and applied to develop a global optimization method for the wastewater treatment network design.
7. By considering of the direct heat recovery that special existing in water using network, a net-heat integration approach for the simultaneous heat and water network integration. And combination with R-PSO algorithms, proposed an evolutionary approach to solve the simultaneous heat and water network optimization problem. By fully taking into account the possibility of the heat recoverie, the proposed approach can realize the optimum energy consumption target and heat exchange network in water using system. Furthermore, as an evolutionary-based approach, the proposed approach can deal with both single and multi-contaminant water-using systems, and can realize the economic trade-off between water network and heat exchanger network.
引文
[1] 胡政. 《水资源与水旱灾研究》: 地震出版社, 1999.
[2] 叶新霞. 区域水资源合理配置及跨流域调水水资源系统问题研究: 河海大学,博士论文, 2005.
[3] 姚荣. 基于可持续发展的区域水资源合理配置研究: 河海大学,博士论文, 2006.
[4] 马元珽. 世界水资源短缺问题的解决. 水利水电快报 2003.
[5] 马永庆. 《黄河水洎水资源论文集(一)》: 黄河水利出版社, 1999.
[6] Mann JG, Liu YA. Industrial water reuse and wastewater minimization. New York, USA: McGraw-Hill., 1999.
[7] Bagajewicz M. A review of recent design procedures for water networks in refineries and process plants. Computer and Chemical Engineering 2000, 24(9):2093-2115.
[8] 李英, 姚平经. 水分配网络设计研究进展. 石油化工 2002, 31(3):224-229.
[9] 都健, 李英, 孟小琼, 樊席山, 姚平经. 水分配网络综合研究. 水科学进展 2003, 14(3):287-289.
[10] Polley GT, Polley HL. Design better water networks. Chemical engineer progress 2000, 96:47-52.
[11] Hallale N. A new graphical targeting method for water minimization. Advances in Environmental research 2002, 6(3):377-390.
[12] Prakash R, Shenoy UV. Targeting and design of water networks for fixed flowrate and fixed contaminant load operations. Chem. Eng. Sci 2005, 60(1):255-268.
[13] Manan ZA, Tan YL, Foo CY. Targeting the minimum water flow rate using water cascade analysis technique. AICHE journal 2005, 50(12):3169-3183.
[14] Wang YP, Smith R. Wastewater minimization. Chem. Eng. Sci 1994, 49(7):981-1006.
[15] Wang YP, Smith R. Wasterwater minimization with flowrate constraints. Chem Eng Res De 1995, 73:889-904.
[16] Kuo WCJ, Smith R. Effuent treament system design. Chem. Eng. Sci 1997, 52(23):4273-4290.
[17] Wang YP, Smith R. Design of distributed effuluent treatment systems. Chem. Eng. Sci 1994, 49(18):3127-3145.
[18] Takama N, Kuriyama T, SHIROKO K, Umeda T. Optimal planning of water allocation in industry. journal of chemical engineering of japan 1980, 13(6):478-483.
[19] Takama N, Kuriyama T, SHIROKO K, Umeda T. Optimal water allocation in a petroleum refinery. Computer and Chemical Engineering 1980, 4:251-258.
[20] Takama N, Kuriyama T, Shiroko K, Umeda T. On the formulation of optimal water allocation problem by linear programming. Computer and Chemical Engineering 1981, 5:119-121.
[21] McLaughin LA, McLaughin HS, Groff KA. Develop an effective watewater treatment strategy. Chemical Engineering Progress 1992:34-42.
[22] Kuo WCJ, Smith R. Design of water-using systems involving regeneration. Trans,IChemE 1998, 76(part A):94.
[23] Kuo WCJ, Smith R. Designing for the interactions between water-use and effluent treatment. Trans,IChemE 1998, Part A(76):287.
[24] Tan R, Cruz DE. Synthis of robust water reuse networks for single-component retrofit problems using symmetric fuzzy linear programmin. Computer and Chemical Engineering 2004, 28(12):2547-2551.
[25] Linnhoff B, Hindmarsh E. The pinch design method for heat exchanger network. Chem. Eng. Sci 1983, 38(5):745.
[26] Linnhoff B, Polley GT, Sahdev V. General process improvements through pinch technology. Chem. Eng. Prog 1988, 84(6):51-58.
[27] Linnhoff B. Pinch analysis-a state-of-the-art overview. Trans. IchemE 1993, 71(A5):503-522.
[28] Holland JH. Adaptation in natural and artificial System. 1975, Ann Arbor:University of michigan press.
[29] Kirkpartrick S, Gelatt D, Vecchi MP. Optimization by simulated annealing. Science 1983, 220:671-680.
[30] Kirkpartrick S. Optimization by simulated annealing:quantitive studies. J Stat Phys 1984, 34:975.
[31] Coldberg A. Genetic algorihms in seach, optimization, and machine learning, reading. 1989, Wesleg:Addison A M.
[32] 鄢烈祥, 麻德贤. 用列队竞争算法求解分离序列综合问题. 化工学报 1999, 13(5):470-475.
[33] Glover F. New future path for integer programming and links to artificial intelligence. Computer Prs Res 1986, 13(5):533.
[34] Glover F. Tabu search-part Ⅰand Ⅱ. ORAS. J. Computer 1989, 1:190-206.
[35] Glover F. A user's guide to Tabu search. Annuals of operation research 1993, 41(3):28.
[36] Dorigo M, Maniezzo V, Colorini. Ant system: optimization by a colony of cooperation agents. IEEE Trans On Systems Man and Cybernetic 1996, 26(1):29-41.
[37] Kennedy J, Eberhart R. Particle swarm optimization. Proc. IEEE international conference on neural networt. Piscataway, NJ: IEEE service center, 1995: 39-43.
[38] 李英. 废水最小化的过程集成研究: 大连理工大学,博士学位论文, 2003.
[39] 都健. 考虑能量集成及柔性的用水网络设计方法研究: 大连理工大学,博士学位论文, 2004.
[40] 李保红. 水分配网络设计与改造方法研究: 大连理工大学,博士学位论文, 2001.
[41] Wang YP, Smith R. Time pinch analysis. Trans, IChemE 1995, Part A:905-914.
[42] Castro P, Matos H, Fernandes MC, Nunes CP. Improvement for mass-exchange networks design. Chem. Eng. Sci 1999, 54(11):1649-1665.
[43] Olesen SG, Polley GT. Dealing with plant geography and piping costraints in water networks. Trans. IchemE 1996, Part A(75):273-276.
[44] Olesen SG, T PG. A simple methodology for the design of water networks handing single contaminant. Trans,IChemE 1997, Part A(75):420-426.
[45] Bagajewicz M, Savelski M. On the optimality conditions of water utilization systems in process plants with single contaminants. Chemical Engineering Science 2000, 55(21):5035-5048.
[46] Savelski M, Bagajewicz M. On the necessary conditions of optimality of water utilization systems in process plants with multiple contaminants. Chem. Eng. Sci 2003, 58(23):5349-5362.
[47] Bagajewicz M, Rivas M, Savelski M. A new approach to the design of utilization systems with multiple contaminants in process plants. Annual AIChE, 1999, Dallas, TX.
[48] Dhole VR, Ramchandani N, Tainsh RA, Wasilewski M. Make your process water pau for iterself. Chem Eng 1996, (6):100-103.
[49] Paul T. Pinch technology reduces wastewater. Chemical Engineering 1996, November:87-90.
[50] El-Halwagi MM, Gabriel F, Harell D. Rigorous graphical targeting for resource conservation via Material recycle/reuse network. Ind. Eng. Chem. Res 2003, 42(19):4319-4328.
[51] Sorin M, Bedard S. The gloable pinch point in water reuse networks. Trans, IChemE 1999, Part B(73):305-308.
[52] Doyle SJ, Smith R. Targeting water reuse with multiple contaminants. Trans,IChemE 1997, 75(part B):181-189.
[53] Alva-Argaez A, Kokossis C, Smith R. Wasterwater Minimization of industrial systems using an integrated approach. Computer and Chemical Engineering 1998, 22(Suppl.):S741-S744.
[54] Alva-Argaez A, Kokossis C, Smith R. Automated design of industrial water network. A.I.C.H.E Annual Meeting 1998, Miami: paper 13 f.
[55] Huang C-H, Chang C, Ling H-C, Chang C-C. A Mathematical Programming Model for Water Usage and Treatment Network Design. Ind. Eng. Chem. Res 1999, 38(7):2666 - 2679.
[56] Benko N, Rev E, Szitkai Z, Fonyo Z. Optimal water use and treatment allocation. Computer and Chemical Engineering 1999, (supp.):S589-S592.
[57] Yang YH, Lou HH, Huang YL. Synthesis of an optimal wastewater reuse network. Waste Mangement 2000, 20(4):311-319.
[58] Lee S, Grossmann IE. Global optimization of nonlinear generalized disjunctive programming with bilinear equality constraints:applications to process networks. Computer and Chemical Engineering 2003, 27:1557.
[59] Lee S, Grossmann IE. A global optimization algorithm for nonconvex generalized disjunctive programming and applications to process systems. Computer and Chemical Engineering 2001, 25(11-12):1675-1697.
[60] Zamoria JM, Grossmann IE. Cotinuous global optimization of structured process system models. Computer and Chemical Engineering 1998, 22:1749.
[61] Galan B, Grossmann IE. Optimal design of distributed wastewater treatment networks. Ind. Eng. Chem. Res 1998, 37(10):4036-4038.
[62] Karuppiah R, Grossmann IE. Global optimization for the synthesis of integrated water systems in chemical processes. Computer and Chemical Engineering 2006, 30(4):650-673.
[63] Rogelio H, Julian C, Zamora J. Superstructure decomposition and parametric optimization approach for the synthesis of distributed wastewater treatment. Ind. Eng. Chem. Res 2004, 43(9):2175-2191.
[64] Chang CT, Li B-h. Improve optimization for general practical water-usage and treatment network structure. Ind. Eng. Chem. Res 2005, 44(10):3607-3618.
[65] 胡仰栋, 徐冬梅, 华贲. 逐步线性规划发求解废水最小化问题. 化工学报 2002, 53(1):66-71.
[66] 乔红梅, 徐冬梅, 胡仰栋, 华贲. 线性规划法确定用水网络最小水用量. 计算机与应用化学 2003, 20(5):601-606.
[67] 徐冬梅, 胡仰栋, 华贲, 王修林. 逐步非线性规划求解多组分废水最小化问题. 计算机与应用化学 2003, 20(6):789-792.
[68] Dongmei X, Yangdong H. Minimization of the flowrate of freshwater and corresponding regenerated water in water-using system with regeneration. Chinese J. Chem. Eng 2003, 11(3):257-263.
[69] 李保红, 费维扬. 分阶段线性规划法快速设计含有多种污染物的用水网络. 化工学报 2005, 56(2):285-290.
[70] Savelski MJ, Bagajewicz M. On the use of linear models for the design of water utilization systems in process plants with a single contaminant. Chemical Engineer Research and Design 2001, Part A(79):600-610.
[71] Gomez J, Savelski M, Bagajewicz M. On a systematic design procedure for single component water utilization systems in process plants. Chemical Engineering Communications 2000, Submitted.
[72] Feng X, Seider WD. New Structure and Design Methodology for Water Networks. Ind. Eng. Chem. Res 2001, 40(26):6140 - 6146.
[73] Wang B, Feng X, Zhang Z. A design methodology for multiple-contaminant water networks with single internal water main. Computer and Chemical Engineering 2003, 27(7):903-911.
[74] Alva-Argaez A, Kokossis C, Smith R. A multi-contaminant trasshipment model for mass exchanger networks and wastewater minimization. Computer and Chemical Engineering 1999, 23:1439-1453.
[75] 李英, 姚平经. 水夹点分析法与数学规划法相结合的用水网络设计. 化工学报 2004, 55(2):220-225.
[76] Li BH, Fan XS, Yao PJ. A New Method for Effluent Treatment System Design. Chinese J. Chem. Eng. 2002, 10(3):273.
[77] Prakotpol D, Srinophakun T. GAPinch: genetic algorithm toolbox for water pinch technology. Chemical Engineering and Processing 2002, 43(2):203-217.
[78] 都健, 王洪卫, 孟小琼, et al. 基于自适应模拟退火算法的多杂质用水网络设计. 计算机与应用化学 2004, 21(1):79-82.
[79] 都健, 王洪卫, 孟小琼, 李英, 姚平经. 基于混合优化算法的多杂质废水回用网络的优化设计. 石油学报(英) 2005, 21(1):68-75.
[80] Yugang L, Fan XS, Shiqiang Z, Shuguang X, Xinshun T. An automatic appoach to design water utilization network. 8th International Symposium on Process Systems Engineering(PSE 2003) 2003 年 8 月, Kunming: 928-933.
[81] Vasile L, Petrica L, Valentin P. Genetic algorithm optimization of water consumption and wastewater network topology. Journal of Clean Production 2005, 13(15):1405-1415.
[82] Tsai M-J, Chang C-T. Water Usage and Treatment Network Design Using Genetic Algorithms. Ind. Eng. Chem. Res 2001, 40(22):4874 - 4888.
[83] Majozi T, Brouckaert C, Buckley CA. A graphical technique for wastewater minimization in batch processes. Journal of enviromental management 2006, 78(4):317-329.
[84] Foo C, Manan Z, Tan YL. Sythesis of maximum water recovery network for batch processes systems. Journal of Clean Production 2005, 13(15):1381-1394.
[85] Almato M, Sanmati E, Espuna A, Puigjaner L. Rationalizing the water reuse in batch process industrie. Computer and Chemical Engineering 1997, 21:S971-976.
[86] Almato M, Sanmati E, Espuna A, Puigjaner L. Optimization of water use in batch process industries. Computer and Chemical Engineering 1999, 23(10):1427-1437.
[87] Almato M, Sanmati E, Espuna A, Puigjaner L. Economic optimization of the water reuse network in batch process industries. Computer and Chemical Engineering 1999, 23:S157-160.
[88] Kim J-K, Smith R. Automated design of discontinuous water systems. Trans, IChemE 2004, part B:238-248.
[89] Majozi T. Wastewater minimization using central reusable water storage in batch plants. computer and Chemical Engineering 2005, 29(7):1631-1646.
[90] Majozi T. An effective technique for wastewater minimisation in batch processes. Journal of Clean Production 2005, 13(15):1374-1380.
[91] Al-Redhwan SA, Crittenden BD, Lababidi HMS. Wastewater minimization under uncertain operational conditions. Computer and Chemical Engineering 2005, 29(5):1009-1021.
[92] Sorin M, Savulescu L. On minimization of the number of heat exchangers in water networks. Heat transfer engineering 2004, 25(5):30-38.
[93] Savulescu LE, Sorin M, Smith R. Direct and indirect heat transfer in water network systems. Applied Thermal engineering 2001, 22(8):981-988.
[94] Savulescu LE, Smith R. Simultaneous energy and water and energy minimization. AICHE Annual Meeting; 1998:Paper 13c.
[95] Savulescu L, Jin-Kuk K, Smith R. Studies on simultaneous energy and water minimization PartⅠ:Systems with no water re-use. Chemical Engineer Science 2005, 60(12):3279-3290.
[96] Savulescu L, Jin-Kuk K, Smith R. Studies on simultaneous energy and water minimization PartⅡ: Systems with maximum re-use of water. Chemical Engineer Science 2005, 60(12):3291-3308.
[97] Savulescu L. Simultaneous energy and water and energy minimization. PHD: UMIST1999.
[98] Bagajewicz M, Rodera H, Savelski M. Energy efficient water utilization systems in process plants. Computer and Chemical Engineering 2002, 26(1):59-79.
[99] Zheng XS, Fen X, Cao DL. Design water allocation network with minimum freshwater and energy consumption. 8thInternational Symposium on Process Systems Engineering 2003, Kunming: 388-393.
[100] Jian D, Pingjing Y, etal. Optimal design of water utilization network with energy integration in process industries. Chinese J. Chem. Eng 2004, 12(2):247-255.
[101] 都健, 孟晓琼, 樊希山, 姚平经. 用水与用能同时最小化的过程综合方法研究. 大连理工大学学报 2003, 43(2):141-146.
[102] Jian D, Hongmei Y, Xishan F, Pingjing Y. Interation of mass and energy in water network design. 8th International Symposium on Process Systems Engineering 2003, Kucuning.
[103] El-Halwagi MM, Manousiousthakis V. Syntheisis of mass exchange network. AICHE Journal 1989, 35(18):1233-1244.
[104] Bagajewicz M, Rivas M, Savelski M. A robust method to obtain optimal and sub-optimal design and retrofit solutions of water utilization systems with multiple contaminants in process plants. Computer and Chemical Engineering 2000, (24):1461-1466.
[105] Savelski M, Bagajewicz M. Algorithmic procedure to design single component water utilization systems in process plants. Chem. Eng. Scie 2001, 56(5):1897-1912.
[106] Prakash R, Shenoy UV. Design and evolution of water networks by source shifts. Chem. Eng. Scie 2005, 60(7):2089-2093.
[107] Gomes JFS, Queiroz EM, Pessoa FLP. Design procedure for water/wastewater minimization: single contaminant. submitted by journal of Clean Production 2006.
[108] Petrides,D, Cruz R, Calandrains J. Optimization of wastewater treatment facilities using process simulation. Computer and Chemical Engineering 1998, 22(Supp):339-346.
[109] Linninger A, Chakraborty. Synthesis and optimization of waste treatment flowsheets. Computer and Chemical Engineering 1999, 23:1415-1425.
[110] Koppol AM, Bagajewicz M, Dericks BJ, Savelski M. On zero water discharge solutions in the process industry. Advances in Environmental research 2003, 8:151-171.
[111] Kemp Y, Deakin A. The cascade analysis for energy and process integration of batch process. Part I:calculation of enengy targets. Chemical Enginneering Research Design 1989, 67:795-509.
[112] 崔明珠, 冯霄, 张文玲等. 间歇过程的热集成. 化学工程 1997, 27(5):48-51.
[113] Grau R, Graells M, Corominas J, Et a. Global strategy for energy and waste anlysis in scheduling and palning of mulitiproduct batch chemical processes. Computer and Chemical Engineering 1996, 20(6-7):853-868.
[114] Foo C, ZA. M, et.al. Sythesis of mass exchage network for batch processes—PartⅠutility targeting. Chemical Engineering Science 2004, 59:1009-1026.
[115] Foo C, Manan Z, Yunus R, Aziz R. Sythesis of mass exchage network for batch processes—PartⅡMinimum units target and batch network design. Chem. Eng. Sci 2005, 60(5):1349-1362.
[116] Foo C, Mann Z, Yunus R, Aziz R. Sythesis of mass exchage network for batch processes—PartⅠutility targeting. Chem. Eng. Sci 2004, 59(5):1009-1026.
[117] Zheng P, Feng X, Qian F, Cao D. Water system integration of a chemical plant. Energy Conversion and Management 2006, 47(15-16):2470-2478.
[118] 徐冬梅. 用水网络设计的研究:博士学位论文. 青岛;中国海洋大学, 2006.
[119] Smith R. Chemical Process Design and Integration: John Wiley & Sons, ltd, 2005.
[120] Smith R. Chemical Process Desig. New York: McGraw Hill, 1995.
[121] Sahinidis NV. Optimization under uncertainty: State-of-the-art and opportunities. Computers and Chemical Engineering 2004, 28(6-7):971–983.
[122] Savelski M, Bagajewicz M. On the use of linear modesl for the design of water utilization systems in refineries and process plants. Chem. Eng. Res.Des 2001, 79(A5):600-610.
[123] Raymond R, Tan R, E.cruz D. Synthis of robust water reuse networks for single-component retrofit problems using symmetric fuzzy linear programming. Computers & Chemical Engineering 2004, 28(12):2547-2551.
[124] Liu YJ, Luo YQ, Yuan XG. An improved MILP model to solve water utilization networks with single contaminants. Proceedings of International symposium on Natural Resource Processing-Science and Technology 2003, Tianjin.
[125] Millpnas MM. Swarm, phase transition and collective intelligence. In C.G. langton, Artificial life III, addison- wesley,MA, 1994.
[126] Kennedy J, Eberhart R. A discrete binary version of the particle swarm algorithm. Proc IEEE Int conf on systems, Man and Cybernetics. 1997, Piscataway: IEEE.
[127] Cardoso MF, Salcedo RL, Azevedo. S Feyode, Barbosa D. A simulated annealing approach to the solution of MINLP problems. Computers & Chemical Engineering 1997, 21:1349–1364.
[128] Kocis GR, I. E Grossmann. Relaxation strategy for the structural optimization of process flow sheets. Industrial & Engineering Chemistry Research. Industrial & Engineering ChemistryResearch 1987, 26(9):1869–1880.
[129] Salcedo RL. Solving nonconvex nonlinear programming problems with adaptive random search. Industrial & Engineering Chemistry Research 1992, 31:262–273.
[130] Costa L, Olivera P. Evolutionary algorithms approach to the solution of mixed integer non-linear programming problems. Computers & Chemical Engineering 2001, 25:257–266.
[131] Kocis GR, Grossmann IE. A modeling and decomposition strategy for the MINLP optimization of process flowsheets. Computer and Chemical Engineering 1989, 13:797-819.
[132] Diwekar UM, Grossmann IE, Rubin ES. An MINLP process synthesizer for a sequential modular simulator. Industrial & Engineering Chemistry Research 1992, 31(313–322.).
[133] Yuan X, Zhang S, Pibouleau L, Domennech S. A mixed-integer nonlinear-programming method for process design. RAIRO-Recherche Operationnelle-Operations Research 1989, 22:331–346.
[134] Babu BV, Angira R. A differential evolution approach for global optimization of MINLP problems. In Proceedings of the 4th Asia-Pacific conference on simulated evolution and learning (SEAL'02), 2002: 866-870.
[135] Ryoo HS, Sahinidis BP. Global optimization of nonconvex NLPs and MINLPs with application in process design. Computers &Chemical Engineering 1995, 19: 551–566.
[136] Hock W, Schittkowski K. Test examples for nonlinear programming codes. Lecture notes in economics and mathematical systems: Vol.187, Berlin, Germany: Spring–Verlag. 1981.
[137] Mezura-Montes E, CoelloCoello CA. A simple multimembered evolution strategy to solve constrained optimization problems. IEEE Transactions on Evolutionary Computation, 2005, 9(1):1-17.
[138] Venkatraman S, Yen GG. A generic framework for constrained optimization using genetic algorithm. IEEE Transactions on Evolutionary Computation 2005, 9(4):424-435.
[139] Koziel S, Michalewicz Z. Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization. Evolutionary computation 1999, 7(1):19-44.
[140] Angantyr A, Andersson J, Aidanpaa JO. Constrained optimization based on a multiobjective evolutionary Algorithm. Evolutionary computation 2003, 3:1560-1567.
[141] 陈中州. 间歇过程与设计的研究: 天津大学硕士学位论文 1996.
[142] 姚兆玲. 考虑环境影响极产品柔性的间歇化工过程最优化研究: 天津大学博士学位论文 2000.
[143] 王举. 间歇化工过程的最优化方法及生产排序研究: 天津大学博士学位论文 2000.
[144] 安为中. 基于随机优化的复杂精馏系统综合研究: 天津大学博士学位论文 2003.
[145] Ahmad S, B.Linnhoff, Smith R. Design of multi-pass heat exchangers: an alternative approach. Trans, ASME, J. Heat transfer 1988, 110(22):304-309.
[2] 叶新霞. 区域水资源合理配置及跨流域调水水资源系统问题研究: 河海大学,博士论文, 2005.
[3] 姚荣. 基于可持续发展的区域水资源合理配置研究: 河海大学,博士论文, 2006.
[4] 马元珽. 世界水资源短缺问题的解决. 水利水电快报 2003.
[5] 马永庆. 《黄河水洎水资源论文集(一)》: 黄河水利出版社, 1999.
[6] Mann JG, Liu YA. Industrial water reuse and wastewater minimization. New York, USA: McGraw-Hill., 1999.
[7] Bagajewicz M. A review of recent design procedures for water networks in refineries and process plants. Computer and Chemical Engineering 2000, 24(9):2093-2115.
[8] 李英, 姚平经. 水分配网络设计研究进展. 石油化工 2002, 31(3):224-229.
[9] 都健, 李英, 孟小琼, 樊席山, 姚平经. 水分配网络综合研究. 水科学进展 2003, 14(3):287-289.
[10] Polley GT, Polley HL. Design better water networks. Chemical engineer progress 2000, 96:47-52.
[11] Hallale N. A new graphical targeting method for water minimization. Advances in Environmental research 2002, 6(3):377-390.
[12] Prakash R, Shenoy UV. Targeting and design of water networks for fixed flowrate and fixed contaminant load operations. Chem. Eng. Sci 2005, 60(1):255-268.
[13] Manan ZA, Tan YL, Foo CY. Targeting the minimum water flow rate using water cascade analysis technique. AICHE journal 2005, 50(12):3169-3183.
[14] Wang YP, Smith R. Wastewater minimization. Chem. Eng. Sci 1994, 49(7):981-1006.
[15] Wang YP, Smith R. Wasterwater minimization with flowrate constraints. Chem Eng Res De 1995, 73:889-904.
[16] Kuo WCJ, Smith R. Effuent treament system design. Chem. Eng. Sci 1997, 52(23):4273-4290.
[17] Wang YP, Smith R. Design of distributed effuluent treatment systems. Chem. Eng. Sci 1994, 49(18):3127-3145.
[18] Takama N, Kuriyama T, SHIROKO K, Umeda T. Optimal planning of water allocation in industry. journal of chemical engineering of japan 1980, 13(6):478-483.
[19] Takama N, Kuriyama T, SHIROKO K, Umeda T. Optimal water allocation in a petroleum refinery. Computer and Chemical Engineering 1980, 4:251-258.
[20] Takama N, Kuriyama T, Shiroko K, Umeda T. On the formulation of optimal water allocation problem by linear programming. Computer and Chemical Engineering 1981, 5:119-121.
[21] McLaughin LA, McLaughin HS, Groff KA. Develop an effective watewater treatment strategy. Chemical Engineering Progress 1992:34-42.
[22] Kuo WCJ, Smith R. Design of water-using systems involving regeneration. Trans,IChemE 1998, 76(part A):94.
[23] Kuo WCJ, Smith R. Designing for the interactions between water-use and effluent treatment. Trans,IChemE 1998, Part A(76):287.
[24] Tan R, Cruz DE. Synthis of robust water reuse networks for single-component retrofit problems using symmetric fuzzy linear programmin. Computer and Chemical Engineering 2004, 28(12):2547-2551.
[25] Linnhoff B, Hindmarsh E. The pinch design method for heat exchanger network. Chem. Eng. Sci 1983, 38(5):745.
[26] Linnhoff B, Polley GT, Sahdev V. General process improvements through pinch technology. Chem. Eng. Prog 1988, 84(6):51-58.
[27] Linnhoff B. Pinch analysis-a state-of-the-art overview. Trans. IchemE 1993, 71(A5):503-522.
[28] Holland JH. Adaptation in natural and artificial System. 1975, Ann Arbor:University of michigan press.
[29] Kirkpartrick S, Gelatt D, Vecchi MP. Optimization by simulated annealing. Science 1983, 220:671-680.
[30] Kirkpartrick S. Optimization by simulated annealing:quantitive studies. J Stat Phys 1984, 34:975.
[31] Coldberg A. Genetic algorihms in seach, optimization, and machine learning, reading. 1989, Wesleg:Addison A M.
[32] 鄢烈祥, 麻德贤. 用列队竞争算法求解分离序列综合问题. 化工学报 1999, 13(5):470-475.
[33] Glover F. New future path for integer programming and links to artificial intelligence. Computer Prs Res 1986, 13(5):533.
[34] Glover F. Tabu search-part Ⅰand Ⅱ. ORAS. J. Computer 1989, 1:190-206.
[35] Glover F. A user's guide to Tabu search. Annuals of operation research 1993, 41(3):28.
[36] Dorigo M, Maniezzo V, Colorini. Ant system: optimization by a colony of cooperation agents. IEEE Trans On Systems Man and Cybernetic 1996, 26(1):29-41.
[37] Kennedy J, Eberhart R. Particle swarm optimization. Proc. IEEE international conference on neural networt. Piscataway, NJ: IEEE service center, 1995: 39-43.
[38] 李英. 废水最小化的过程集成研究: 大连理工大学,博士学位论文, 2003.
[39] 都健. 考虑能量集成及柔性的用水网络设计方法研究: 大连理工大学,博士学位论文, 2004.
[40] 李保红. 水分配网络设计与改造方法研究: 大连理工大学,博士学位论文, 2001.
[41] Wang YP, Smith R. Time pinch analysis. Trans, IChemE 1995, Part A:905-914.
[42] Castro P, Matos H, Fernandes MC, Nunes CP. Improvement for mass-exchange networks design. Chem. Eng. Sci 1999, 54(11):1649-1665.
[43] Olesen SG, Polley GT. Dealing with plant geography and piping costraints in water networks. Trans. IchemE 1996, Part A(75):273-276.
[44] Olesen SG, T PG. A simple methodology for the design of water networks handing single contaminant. Trans,IChemE 1997, Part A(75):420-426.
[45] Bagajewicz M, Savelski M. On the optimality conditions of water utilization systems in process plants with single contaminants. Chemical Engineering Science 2000, 55(21):5035-5048.
[46] Savelski M, Bagajewicz M. On the necessary conditions of optimality of water utilization systems in process plants with multiple contaminants. Chem. Eng. Sci 2003, 58(23):5349-5362.
[47] Bagajewicz M, Rivas M, Savelski M. A new approach to the design of utilization systems with multiple contaminants in process plants. Annual AIChE, 1999, Dallas, TX.
[48] Dhole VR, Ramchandani N, Tainsh RA, Wasilewski M. Make your process water pau for iterself. Chem Eng 1996, (6):100-103.
[49] Paul T. Pinch technology reduces wastewater. Chemical Engineering 1996, November:87-90.
[50] El-Halwagi MM, Gabriel F, Harell D. Rigorous graphical targeting for resource conservation via Material recycle/reuse network. Ind. Eng. Chem. Res 2003, 42(19):4319-4328.
[51] Sorin M, Bedard S. The gloable pinch point in water reuse networks. Trans, IChemE 1999, Part B(73):305-308.
[52] Doyle SJ, Smith R. Targeting water reuse with multiple contaminants. Trans,IChemE 1997, 75(part B):181-189.
[53] Alva-Argaez A, Kokossis C, Smith R. Wasterwater Minimization of industrial systems using an integrated approach. Computer and Chemical Engineering 1998, 22(Suppl.):S741-S744.
[54] Alva-Argaez A, Kokossis C, Smith R. Automated design of industrial water network. A.I.C.H.E Annual Meeting 1998, Miami: paper 13 f.
[55] Huang C-H, Chang C, Ling H-C, Chang C-C. A Mathematical Programming Model for Water Usage and Treatment Network Design. Ind. Eng. Chem. Res 1999, 38(7):2666 - 2679.
[56] Benko N, Rev E, Szitkai Z, Fonyo Z. Optimal water use and treatment allocation. Computer and Chemical Engineering 1999, (supp.):S589-S592.
[57] Yang YH, Lou HH, Huang YL. Synthesis of an optimal wastewater reuse network. Waste Mangement 2000, 20(4):311-319.
[58] Lee S, Grossmann IE. Global optimization of nonlinear generalized disjunctive programming with bilinear equality constraints:applications to process networks. Computer and Chemical Engineering 2003, 27:1557.
[59] Lee S, Grossmann IE. A global optimization algorithm for nonconvex generalized disjunctive programming and applications to process systems. Computer and Chemical Engineering 2001, 25(11-12):1675-1697.
[60] Zamoria JM, Grossmann IE. Cotinuous global optimization of structured process system models. Computer and Chemical Engineering 1998, 22:1749.
[61] Galan B, Grossmann IE. Optimal design of distributed wastewater treatment networks. Ind. Eng. Chem. Res 1998, 37(10):4036-4038.
[62] Karuppiah R, Grossmann IE. Global optimization for the synthesis of integrated water systems in chemical processes. Computer and Chemical Engineering 2006, 30(4):650-673.
[63] Rogelio H, Julian C, Zamora J. Superstructure decomposition and parametric optimization approach for the synthesis of distributed wastewater treatment. Ind. Eng. Chem. Res 2004, 43(9):2175-2191.
[64] Chang CT, Li B-h. Improve optimization for general practical water-usage and treatment network structure. Ind. Eng. Chem. Res 2005, 44(10):3607-3618.
[65] 胡仰栋, 徐冬梅, 华贲. 逐步线性规划发求解废水最小化问题. 化工学报 2002, 53(1):66-71.
[66] 乔红梅, 徐冬梅, 胡仰栋, 华贲. 线性规划法确定用水网络最小水用量. 计算机与应用化学 2003, 20(5):601-606.
[67] 徐冬梅, 胡仰栋, 华贲, 王修林. 逐步非线性规划求解多组分废水最小化问题. 计算机与应用化学 2003, 20(6):789-792.
[68] Dongmei X, Yangdong H. Minimization of the flowrate of freshwater and corresponding regenerated water in water-using system with regeneration. Chinese J. Chem. Eng 2003, 11(3):257-263.
[69] 李保红, 费维扬. 分阶段线性规划法快速设计含有多种污染物的用水网络. 化工学报 2005, 56(2):285-290.
[70] Savelski MJ, Bagajewicz M. On the use of linear models for the design of water utilization systems in process plants with a single contaminant. Chemical Engineer Research and Design 2001, Part A(79):600-610.
[71] Gomez J, Savelski M, Bagajewicz M. On a systematic design procedure for single component water utilization systems in process plants. Chemical Engineering Communications 2000, Submitted.
[72] Feng X, Seider WD. New Structure and Design Methodology for Water Networks. Ind. Eng. Chem. Res 2001, 40(26):6140 - 6146.
[73] Wang B, Feng X, Zhang Z. A design methodology for multiple-contaminant water networks with single internal water main. Computer and Chemical Engineering 2003, 27(7):903-911.
[74] Alva-Argaez A, Kokossis C, Smith R. A multi-contaminant trasshipment model for mass exchanger networks and wastewater minimization. Computer and Chemical Engineering 1999, 23:1439-1453.
[75] 李英, 姚平经. 水夹点分析法与数学规划法相结合的用水网络设计. 化工学报 2004, 55(2):220-225.
[76] Li BH, Fan XS, Yao PJ. A New Method for Effluent Treatment System Design. Chinese J. Chem. Eng. 2002, 10(3):273.
[77] Prakotpol D, Srinophakun T. GAPinch: genetic algorithm toolbox for water pinch technology. Chemical Engineering and Processing 2002, 43(2):203-217.
[78] 都健, 王洪卫, 孟小琼, et al. 基于自适应模拟退火算法的多杂质用水网络设计. 计算机与应用化学 2004, 21(1):79-82.
[79] 都健, 王洪卫, 孟小琼, 李英, 姚平经. 基于混合优化算法的多杂质废水回用网络的优化设计. 石油学报(英) 2005, 21(1):68-75.
[80] Yugang L, Fan XS, Shiqiang Z, Shuguang X, Xinshun T. An automatic appoach to design water utilization network. 8th International Symposium on Process Systems Engineering(PSE 2003) 2003 年 8 月, Kunming: 928-933.
[81] Vasile L, Petrica L, Valentin P. Genetic algorithm optimization of water consumption and wastewater network topology. Journal of Clean Production 2005, 13(15):1405-1415.
[82] Tsai M-J, Chang C-T. Water Usage and Treatment Network Design Using Genetic Algorithms. Ind. Eng. Chem. Res 2001, 40(22):4874 - 4888.
[83] Majozi T, Brouckaert C, Buckley CA. A graphical technique for wastewater minimization in batch processes. Journal of enviromental management 2006, 78(4):317-329.
[84] Foo C, Manan Z, Tan YL. Sythesis of maximum water recovery network for batch processes systems. Journal of Clean Production 2005, 13(15):1381-1394.
[85] Almato M, Sanmati E, Espuna A, Puigjaner L. Rationalizing the water reuse in batch process industrie. Computer and Chemical Engineering 1997, 21:S971-976.
[86] Almato M, Sanmati E, Espuna A, Puigjaner L. Optimization of water use in batch process industries. Computer and Chemical Engineering 1999, 23(10):1427-1437.
[87] Almato M, Sanmati E, Espuna A, Puigjaner L. Economic optimization of the water reuse network in batch process industries. Computer and Chemical Engineering 1999, 23:S157-160.
[88] Kim J-K, Smith R. Automated design of discontinuous water systems. Trans, IChemE 2004, part B:238-248.
[89] Majozi T. Wastewater minimization using central reusable water storage in batch plants. computer and Chemical Engineering 2005, 29(7):1631-1646.
[90] Majozi T. An effective technique for wastewater minimisation in batch processes. Journal of Clean Production 2005, 13(15):1374-1380.
[91] Al-Redhwan SA, Crittenden BD, Lababidi HMS. Wastewater minimization under uncertain operational conditions. Computer and Chemical Engineering 2005, 29(5):1009-1021.
[92] Sorin M, Savulescu L. On minimization of the number of heat exchangers in water networks. Heat transfer engineering 2004, 25(5):30-38.
[93] Savulescu LE, Sorin M, Smith R. Direct and indirect heat transfer in water network systems. Applied Thermal engineering 2001, 22(8):981-988.
[94] Savulescu LE, Smith R. Simultaneous energy and water and energy minimization. AICHE Annual Meeting; 1998:Paper 13c.
[95] Savulescu L, Jin-Kuk K, Smith R. Studies on simultaneous energy and water minimization PartⅠ:Systems with no water re-use. Chemical Engineer Science 2005, 60(12):3279-3290.
[96] Savulescu L, Jin-Kuk K, Smith R. Studies on simultaneous energy and water minimization PartⅡ: Systems with maximum re-use of water. Chemical Engineer Science 2005, 60(12):3291-3308.
[97] Savulescu L. Simultaneous energy and water and energy minimization. PHD: UMIST1999.
[98] Bagajewicz M, Rodera H, Savelski M. Energy efficient water utilization systems in process plants. Computer and Chemical Engineering 2002, 26(1):59-79.
[99] Zheng XS, Fen X, Cao DL. Design water allocation network with minimum freshwater and energy consumption. 8thInternational Symposium on Process Systems Engineering 2003, Kunming: 388-393.
[100] Jian D, Pingjing Y, etal. Optimal design of water utilization network with energy integration in process industries. Chinese J. Chem. Eng 2004, 12(2):247-255.
[101] 都健, 孟晓琼, 樊希山, 姚平经. 用水与用能同时最小化的过程综合方法研究. 大连理工大学学报 2003, 43(2):141-146.
[102] Jian D, Hongmei Y, Xishan F, Pingjing Y. Interation of mass and energy in water network design. 8th International Symposium on Process Systems Engineering 2003, Kucuning.
[103] El-Halwagi MM, Manousiousthakis V. Syntheisis of mass exchange network. AICHE Journal 1989, 35(18):1233-1244.
[104] Bagajewicz M, Rivas M, Savelski M. A robust method to obtain optimal and sub-optimal design and retrofit solutions of water utilization systems with multiple contaminants in process plants. Computer and Chemical Engineering 2000, (24):1461-1466.
[105] Savelski M, Bagajewicz M. Algorithmic procedure to design single component water utilization systems in process plants. Chem. Eng. Scie 2001, 56(5):1897-1912.
[106] Prakash R, Shenoy UV. Design and evolution of water networks by source shifts. Chem. Eng. Scie 2005, 60(7):2089-2093.
[107] Gomes JFS, Queiroz EM, Pessoa FLP. Design procedure for water/wastewater minimization: single contaminant. submitted by journal of Clean Production 2006.
[108] Petrides,D, Cruz R, Calandrains J. Optimization of wastewater treatment facilities using process simulation. Computer and Chemical Engineering 1998, 22(Supp):339-346.
[109] Linninger A, Chakraborty. Synthesis and optimization of waste treatment flowsheets. Computer and Chemical Engineering 1999, 23:1415-1425.
[110] Koppol AM, Bagajewicz M, Dericks BJ, Savelski M. On zero water discharge solutions in the process industry. Advances in Environmental research 2003, 8:151-171.
[111] Kemp Y, Deakin A. The cascade analysis for energy and process integration of batch process. Part I:calculation of enengy targets. Chemical Enginneering Research Design 1989, 67:795-509.
[112] 崔明珠, 冯霄, 张文玲等. 间歇过程的热集成. 化学工程 1997, 27(5):48-51.
[113] Grau R, Graells M, Corominas J, Et a. Global strategy for energy and waste anlysis in scheduling and palning of mulitiproduct batch chemical processes. Computer and Chemical Engineering 1996, 20(6-7):853-868.
[114] Foo C, ZA. M, et.al. Sythesis of mass exchage network for batch processes—PartⅠutility targeting. Chemical Engineering Science 2004, 59:1009-1026.
[115] Foo C, Manan Z, Yunus R, Aziz R. Sythesis of mass exchage network for batch processes—PartⅡMinimum units target and batch network design. Chem. Eng. Sci 2005, 60(5):1349-1362.
[116] Foo C, Mann Z, Yunus R, Aziz R. Sythesis of mass exchage network for batch processes—PartⅠutility targeting. Chem. Eng. Sci 2004, 59(5):1009-1026.
[117] Zheng P, Feng X, Qian F, Cao D. Water system integration of a chemical plant. Energy Conversion and Management 2006, 47(15-16):2470-2478.
[118] 徐冬梅. 用水网络设计的研究:博士学位论文. 青岛;中国海洋大学, 2006.
[119] Smith R. Chemical Process Design and Integration: John Wiley & Sons, ltd, 2005.
[120] Smith R. Chemical Process Desig. New York: McGraw Hill, 1995.
[121] Sahinidis NV. Optimization under uncertainty: State-of-the-art and opportunities. Computers and Chemical Engineering 2004, 28(6-7):971–983.
[122] Savelski M, Bagajewicz M. On the use of linear modesl for the design of water utilization systems in refineries and process plants. Chem. Eng. Res.Des 2001, 79(A5):600-610.
[123] Raymond R, Tan R, E.cruz D. Synthis of robust water reuse networks for single-component retrofit problems using symmetric fuzzy linear programming. Computers & Chemical Engineering 2004, 28(12):2547-2551.
[124] Liu YJ, Luo YQ, Yuan XG. An improved MILP model to solve water utilization networks with single contaminants. Proceedings of International symposium on Natural Resource Processing-Science and Technology 2003, Tianjin.
[125] Millpnas MM. Swarm, phase transition and collective intelligence. In C.G. langton, Artificial life III, addison- wesley,MA, 1994.
[126] Kennedy J, Eberhart R. A discrete binary version of the particle swarm algorithm. Proc IEEE Int conf on systems, Man and Cybernetics. 1997, Piscataway: IEEE.
[127] Cardoso MF, Salcedo RL, Azevedo. S Feyode, Barbosa D. A simulated annealing approach to the solution of MINLP problems. Computers & Chemical Engineering 1997, 21:1349–1364.
[128] Kocis GR, I. E Grossmann. Relaxation strategy for the structural optimization of process flow sheets. Industrial & Engineering Chemistry Research. Industrial & Engineering ChemistryResearch 1987, 26(9):1869–1880.
[129] Salcedo RL. Solving nonconvex nonlinear programming problems with adaptive random search. Industrial & Engineering Chemistry Research 1992, 31:262–273.
[130] Costa L, Olivera P. Evolutionary algorithms approach to the solution of mixed integer non-linear programming problems. Computers & Chemical Engineering 2001, 25:257–266.
[131] Kocis GR, Grossmann IE. A modeling and decomposition strategy for the MINLP optimization of process flowsheets. Computer and Chemical Engineering 1989, 13:797-819.
[132] Diwekar UM, Grossmann IE, Rubin ES. An MINLP process synthesizer for a sequential modular simulator. Industrial & Engineering Chemistry Research 1992, 31(313–322.).
[133] Yuan X, Zhang S, Pibouleau L, Domennech S. A mixed-integer nonlinear-programming method for process design. RAIRO-Recherche Operationnelle-Operations Research 1989, 22:331–346.
[134] Babu BV, Angira R. A differential evolution approach for global optimization of MINLP problems. In Proceedings of the 4th Asia-Pacific conference on simulated evolution and learning (SEAL'02), 2002: 866-870.
[135] Ryoo HS, Sahinidis BP. Global optimization of nonconvex NLPs and MINLPs with application in process design. Computers &Chemical Engineering 1995, 19: 551–566.
[136] Hock W, Schittkowski K. Test examples for nonlinear programming codes. Lecture notes in economics and mathematical systems: Vol.187, Berlin, Germany: Spring–Verlag. 1981.
[137] Mezura-Montes E, CoelloCoello CA. A simple multimembered evolution strategy to solve constrained optimization problems. IEEE Transactions on Evolutionary Computation, 2005, 9(1):1-17.
[138] Venkatraman S, Yen GG. A generic framework for constrained optimization using genetic algorithm. IEEE Transactions on Evolutionary Computation 2005, 9(4):424-435.
[139] Koziel S, Michalewicz Z. Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization. Evolutionary computation 1999, 7(1):19-44.
[140] Angantyr A, Andersson J, Aidanpaa JO. Constrained optimization based on a multiobjective evolutionary Algorithm. Evolutionary computation 2003, 3:1560-1567.
[141] 陈中州. 间歇过程与设计的研究: 天津大学硕士学位论文 1996.
[142] 姚兆玲. 考虑环境影响极产品柔性的间歇化工过程最优化研究: 天津大学博士学位论文 2000.
[143] 王举. 间歇化工过程的最优化方法及生产排序研究: 天津大学博士学位论文 2000.
[144] 安为中. 基于随机优化的复杂精馏系统综合研究: 天津大学博士学位论文 2003.
[145] Ahmad S, B.Linnhoff, Smith R. Design of multi-pass heat exchangers: an alternative approach. Trans, ASME, J. Heat transfer 1988, 110(22):304-309.