项目集合选择优化理论、方法与创新研究
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摘要
项目集合选择问题可以表述为这样一类问题：存在一个含有限项目的备择项目集合，其中每个项目都具有两方面的属性，既耗费一定量的各种资源，又在多个目标上具有产出。那么如何在给定的资源约束下确定一个最优的项目组合，使得该项目组合给决策者带来最大的效用。项目集合选择问题涉及了经济管理领域、工程建设领域、工业生产领域的诸多方面。如投资决策中的投资组合设计，信息化建设中的方案设计，公共财政中的预算制订以及工程建设中的项目优化都离不开项目集合选择理论的支持。但是现有关于项目集合选择的理论研究还比较薄弱，绝大多数研究都只是局限于可表示为线性规划形式的一些简单问题，还远远不能满足实际问题求解的需要。
针对这一缺陷，在分析和总结项目集合选择问题一般理论框架的基础上，本文从非线性项目集合选择问题的求解、相关性项目集合选择问题的求解、项目集合选择问题的非参数方法以及序数型指标项目集合选择问题的解法四个方面对项目集合选择的理论进行了一些扩展研究，其具体内容如下：
文章的第一章介绍了项目集合选择问题的定义、一般数学形式以及规划形式，给出了项目集合选择问题求解的一般步骤和常用解法。并且依据项目集合选择问题目标函数和约束条件的特点，构建了项目集合选择问题的分类体系。从整体上研究了项目集合选择问题的一般理论框架。并在分析相关理论的国内外研究现状和缺陷的基础上，给出了本文的研究意义，研究内容、研究思路和主要创新点。
随后，文章的第二章分析了投资方案组合选择问题的非线性特性，建立了该类问题的动态规划模型。在此模型的基础上文章给出了基于外点法求解此类问题的改进贪婪搜索算法。并研究了采用surrogate松弛模型确定初始点和运用改进的贪婪算法搜索最优解的具体实现方法，给出了实现算法的具体步骤。
在文章第三章中，文章讨论了备择项目之间的相关性对项目集合选择问题的最终结果的影响。并构建了一个改进的项目相关性的定义和度量体系。在此相关性定义体系的基础上，文章构建了相关性条件下项目集合选择问题的非线性模型，并给出了非线性模型的线性化方法和具体的算例。
在第四章中，文章分析比较了多目标项目集合选择问题的两类求解方法：参数方法和非参数方法，讨论了参数方法的缺陷。在此基础上，文章提出了多目标项目集合选择问题DEA解法的基本思路，并给出了相应的求解多目标项目集合选择的DEA模型。另外，文章利用第三章中关于相关性项目选择问题建模的有关成
果，提出了相关性条件下项目集合选择的DEA方法和模型。
许多实际的项目集合选择问题中常常含有序数型的指标，对于这类序数型指标项目集合选择问题，目前还缺乏成熟的解法。对此，在第五章中，文章提出了一种“通过建立序数指标评价模型，将序数型指标项目集合选择问题转化为基数型项目集合选择问题，然后求解”的基本思路。并给出了具体的模型和算例。
以上是对项目集合选择问题的一些理论探讨。另外，项目集合选择问题具有一个特性，就是问题的可行解数目随着初始备择项目集合中元素个数的增加呈指数式增长。减少备择项目个数是减少项目集合选择问题计算复杂度的有效手段。文章结合项目集合选择问题的特点改进了单项目选优问题筛选方法中的“有效”，“支配”等概念，提出了“最优筛选”的概念，并在此基础上建立了项目集合选择问题的筛选规则和筛选模型，给出了计算实例。
Subset selection problem can be described as: There is a set including limited amount of projects, which have two features, consuming a certain amount of resources and output a certain amount of outcome in given objects. Then how to determine a optimal portfolio of projects, which can maximize the utility of decision-maker, within a given resource constraints. Various fields, including economics management, project construction, industry production, etc., are involving with subset selection problem. For instance, the investment portfolio design in the field of investment decision making, the plan design in the field of information system construction, budgeting problem in the field of public finance and projects optimization in the field of project construction are only a part of the applications of subset selection theory. Nevertheless, the researches on subset selection theory are considerable deficient, and most of them are limited to linear programming form. These researches cannot meet the demand of solving practical problems.
Aiming at these weaknesses, the study on non-linear subset selection problem, subset selection problem with interdependence, the non-parametric method for subset selection problem and subset selection problem with ordinal criteria is addressed in this dissertation, based on the analysis and summarizing the general theory framework of subset selection problem.
The conception, definition, general mathematic form, and programming form of subset selection problem are addressed in the first chapter of the dissertation. Then, according to the feature of objective function and the constraints, the classification system of the subset selection problem is constructed. The overall theory framework of subset selection theory is introduced. In accordance with the weakness of the researches on the subset selection problem, the purpose, content, outline and innovation of the dissertation is given.
Then, based on the analysis of the non-linear feature of the investment portfolio selection problem, a dynamic programming model is formulated. After that, an exterior point heuristic algorithm is constructed to solve the model. The surrogate model to determine original point and advanced greedy search algorithm to obtain optimal point are discussed, and the whole processes of the algorithm are addressed.
In the third chapter, the crucial effect of the interdependence among the projects is discussed. And a group of definitions and theorems is given to build a definition and measurement system of interdependence phenomena. After that, a non-linear programming model of subset selection problem with interdependence is formulated, and the linearization method for the non-linear model is given. Finally, an application of the model is given.
In the fourth chapter, two methods for solving multi-objective subset selection problem: parametric and nonparametric are compared, and the shortcoming of parametric method is analyzed. Based on these, the general idea of the DEA model to solve multi-objective subset selection problem is proposed and corresponding model is constructed. After that, utilizing the outcome of the chapter three, a DEA model to solve subset selection problem with interdependence is formulated.
Ordinal criteria are often used in many practical subset selection problems. There are scarce effective methods to solving this kind of problems. Aiming at this, an idea to solve the problems is proposed. That is transforming the subset selection problem with ordinal criteria to the problem with cardinal criteria and then solving the problem. Finally the concrete model and an application are given.
Some theoretical study is give hereinbefore. After that, one feature of the subset selection problem, which is that the number of feasible solutions of the subset selection problem will exponentially increase with the increase of the number original projects for selection. So, the most effective way to decrease the computer complexity of the subset selection problem is eliminating the origin
针对这一缺陷，在分析和总结项目集合选择问题一般理论框架的基础上，本文从非线性项目集合选择问题的求解、相关性项目集合选择问题的求解、项目集合选择问题的非参数方法以及序数型指标项目集合选择问题的解法四个方面对项目集合选择的理论进行了一些扩展研究，其具体内容如下：
文章的第一章介绍了项目集合选择问题的定义、一般数学形式以及规划形式，给出了项目集合选择问题求解的一般步骤和常用解法。并且依据项目集合选择问题目标函数和约束条件的特点，构建了项目集合选择问题的分类体系。从整体上研究了项目集合选择问题的一般理论框架。并在分析相关理论的国内外研究现状和缺陷的基础上，给出了本文的研究意义，研究内容、研究思路和主要创新点。
随后，文章的第二章分析了投资方案组合选择问题的非线性特性，建立了该类问题的动态规划模型。在此模型的基础上文章给出了基于外点法求解此类问题的改进贪婪搜索算法。并研究了采用surrogate松弛模型确定初始点和运用改进的贪婪算法搜索最优解的具体实现方法，给出了实现算法的具体步骤。
在文章第三章中，文章讨论了备择项目之间的相关性对项目集合选择问题的最终结果的影响。并构建了一个改进的项目相关性的定义和度量体系。在此相关性定义体系的基础上，文章构建了相关性条件下项目集合选择问题的非线性模型，并给出了非线性模型的线性化方法和具体的算例。
在第四章中，文章分析比较了多目标项目集合选择问题的两类求解方法：参数方法和非参数方法，讨论了参数方法的缺陷。在此基础上，文章提出了多目标项目集合选择问题DEA解法的基本思路，并给出了相应的求解多目标项目集合选择的DEA模型。另外，文章利用第三章中关于相关性项目选择问题建模的有关成
果，提出了相关性条件下项目集合选择的DEA方法和模型。
许多实际的项目集合选择问题中常常含有序数型的指标，对于这类序数型指标项目集合选择问题，目前还缺乏成熟的解法。对此，在第五章中，文章提出了一种“通过建立序数指标评价模型，将序数型指标项目集合选择问题转化为基数型项目集合选择问题，然后求解”的基本思路。并给出了具体的模型和算例。
以上是对项目集合选择问题的一些理论探讨。另外，项目集合选择问题具有一个特性，就是问题的可行解数目随着初始备择项目集合中元素个数的增加呈指数式增长。减少备择项目个数是减少项目集合选择问题计算复杂度的有效手段。文章结合项目集合选择问题的特点改进了单项目选优问题筛选方法中的“有效”，“支配”等概念，提出了“最优筛选”的概念，并在此基础上建立了项目集合选择问题的筛选规则和筛选模型，给出了计算实例。
Subset selection problem can be described as: There is a set including limited amount of projects, which have two features, consuming a certain amount of resources and output a certain amount of outcome in given objects. Then how to determine a optimal portfolio of projects, which can maximize the utility of decision-maker, within a given resource constraints. Various fields, including economics management, project construction, industry production, etc., are involving with subset selection problem. For instance, the investment portfolio design in the field of investment decision making, the plan design in the field of information system construction, budgeting problem in the field of public finance and projects optimization in the field of project construction are only a part of the applications of subset selection theory. Nevertheless, the researches on subset selection theory are considerable deficient, and most of them are limited to linear programming form. These researches cannot meet the demand of solving practical problems.
Aiming at these weaknesses, the study on non-linear subset selection problem, subset selection problem with interdependence, the non-parametric method for subset selection problem and subset selection problem with ordinal criteria is addressed in this dissertation, based on the analysis and summarizing the general theory framework of subset selection problem.
The conception, definition, general mathematic form, and programming form of subset selection problem are addressed in the first chapter of the dissertation. Then, according to the feature of objective function and the constraints, the classification system of the subset selection problem is constructed. The overall theory framework of subset selection theory is introduced. In accordance with the weakness of the researches on the subset selection problem, the purpose, content, outline and innovation of the dissertation is given.
Then, based on the analysis of the non-linear feature of the investment portfolio selection problem, a dynamic programming model is formulated. After that, an exterior point heuristic algorithm is constructed to solve the model. The surrogate model to determine original point and advanced greedy search algorithm to obtain optimal point are discussed, and the whole processes of the algorithm are addressed.
In the third chapter, the crucial effect of the interdependence among the projects is discussed. And a group of definitions and theorems is given to build a definition and measurement system of interdependence phenomena. After that, a non-linear programming model of subset selection problem with interdependence is formulated, and the linearization method for the non-linear model is given. Finally, an application of the model is given.
In the fourth chapter, two methods for solving multi-objective subset selection problem: parametric and nonparametric are compared, and the shortcoming of parametric method is analyzed. Based on these, the general idea of the DEA model to solve multi-objective subset selection problem is proposed and corresponding model is constructed. After that, utilizing the outcome of the chapter three, a DEA model to solve subset selection problem with interdependence is formulated.
Ordinal criteria are often used in many practical subset selection problems. There are scarce effective methods to solving this kind of problems. Aiming at this, an idea to solve the problems is proposed. That is transforming the subset selection problem with ordinal criteria to the problem with cardinal criteria and then solving the problem. Finally the concrete model and an application are given.
Some theoretical study is give hereinbefore. After that, one feature of the subset selection problem, which is that the number of feasible solutions of the subset selection problem will exponentially increase with the increase of the number original projects for selection. So, the most effective way to decrease the computer complexity of the subset selection problem is eliminating the origin
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82．STPP, Surface Transportation Policy Project, 1998. Potholes and politics. Washington, DC. Available at http://www.transact.org/Reports/Potholes/title.htm.
83．STPP, Surface Transportation Policy Project, 2000. Changing direction-Federal transportation spending in the 1990s.Washington, DC. Available at http://www.transact.org/Reports/Cd/tea21color.pdf.
84．Visee M., Teghem J. , Pirlot M., Ulungu E.L., 1998. Two phases method and branch and bound to solve bi-objective knapsack problem. Journal of Global Optimization 12, 139–155.
85．D. Pisinger, Budgeting with bounded multiple-choice constraints, in: Proceedings of AIRO'96, Perugia, 17-20 September 1996.
86．S. Rajabi, D.M. Kilgour, K.W. Hipel. Modeling action-interdependence in multiple criteria decision making, European Journal of Operational Research. 1998;110:490-508
87．D.A. Aaker, T.T. Tyebjee. A model for the selection of interdependent R&D projects. IEEE Transitions on Engineering Management 1978;25:30-36
88．G.W. Evans, R. Fairbairn. Selection and scheduling of advanced missions for NASA using 0-1 integer linear programming. Journal of the Operational Research Society. 1989;40:971-981
89． L.F.A. Gomes. Modeling interdependence among urban transportation system alternatives within a multicriteria ranking framework. Journal of Advanced Transportation. 1992;24:77-85
90．G.H. Tzeng, J.Y. Teng. Transportation investment projects selection with fuzzy multiobjectives. Transportation Planning and Technology. 1993;17:91-112
91．Gupta. S.K., Kyparisis J., Ip. C. Project selection and sequencing to maximize the net present value of total return. Management Science. 1992;38:757-752
92．Ibaraki. T. Enumerative approaches to combinational optimization-Part I. Special Issue of Operations Research 1987;10
93．Ibaraki. T. Enumerative approaches to combinational optimization-Part II. Special Issue of
Operations Research 1987;10
94．Ibaraki. T. Resource allocation problems: algorithmic approaches. MIT Press, Cambridge MA, 1988
95．Gupta. S.K., Kyparisis J., Ip. C. Project selection with discounted returns and multiple constraints. European Journal of Operational Research. 1996;94:87-96
96．Merkhofer M. W., Keeney R. L. A multiattribute utility analysis of alternative sites for the disposal of nuclear waste. Risk Analysis,1987;7:173-193
97．Rajabi S., Hipel K.W., Kilgour D.M. Multiple objective water supply planning. Proc. of International Conference on Water Research & Environmental Research: Towards the 21st Century. 1996;2:167-174
98．Fishburn P.C., LaValle I.H. Binary interactions and subset choice. European Journal of Operational Research. 1996;92:182-192
99．Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units.
100．Saaty, T.L The Analytic Hierarchy Process. McGrawHill, New York 1980
101．Roubens, M. Preference relations on actions and criteria in multicriteria decision making. European Journal of Operational Research 1982;10: 51-55.
102．Korhonen, P. Wallenius, J., and Zionts, S. Solving the discrete multiple criteria problem using convex cones. Management Science. 1984;30/11,1336-1345
103．KoKsalan, M., Karwan, M.H. and Zionts, S. An approach for solving discrete alternative multiple criteria problem involving ordinal criteria. Naval Research Logistics Quarterly. 1988;35/6,625-641
104．高天 翟延慧. 特殊多维0－1背包问题的约束简化方法－不等式单约束生成法. 东北师大学报：自然科学版.2002,34(3).-21-26
105．刘红卫 徐凤敏. 二次背包问题的半定规划松驰. 西安电子科技大学学报. 2001,28(5).-638-640,658
106．胡欣 汪红星. 求解多维0-1背包问题的混合遗传算法. 计算机工程与应用. 1999,35(11).-31-33
107．张立昂 李路阳. 多背包问题近似计算的复杂性. 科学通报.1996,41(20).-1896-1898
108．李庆华 李肯立 蒋盛益 张薇. 背包问题的最优并行算法. 软件学报.2003,14(5).-891-896
109．刘西奎 李艳. 背包问题的遗传算法求解. 华中科技大学学报：自然科学版. 2002,30(6).-89-90
110．程泽 寇纪淞. 一种基于免疫思想的混合式遗传算法.天津理工学院学报. 2001,17(4).-16-19
111．刘娜 钟求喜. 求解0－1背包问题的共同进化遗传算法. 计算机科
学.2001,28(9).-102-105
112．夏洁 高金源. 基于禁忌搜索的启发式任务路径规划算法. 控制与决策. 2002,17 (B11).-773-776
113．贺一 刘光远. 禁忌搜索算法求解旅行商问题研究. 西南师范大学学报：自然科学版. 2002,27(3).-341-345
114．邵亮 陈嫦娟. Tabu搜索算法在电话网智能管理中的应用. 软件学报. 2002,13(8). -1705-1709
115．温平川 徐晓东. 并行遗行／模拟退火混合算法及其应用. 计算机科学.2003,30(3).-86-89
116．范晔 周泓. 作业排序模拟退火算法影响因素分析和一种多次淬火模拟退火法. 系统工程理论方法应用.2003,12(1).-72-76
117．谢传泉 何晨. 混沌神经网络模型中的模拟退火策略. 上海交通大学学报. 2003,37(3) -323-326
118．蒋建国 骆正虎. 基于改进型蚁群算求解旅行Agent问题. 模式识别与人工智能.2003,16(1).-6-11
119．覃刚力 杨家本. 自适应调整信息素的蚁群算法. 信息与控制.2002,31(3).-198-201,210
120．郭彤城 慕春棣. 并行遗传算法的新进展. 系统工程理论与实践.2002,22(2).-15-23,41
121．吴育华 付永进. 决策、对策与冲突分析，海口：南方出版社，2001
122．吴育华 杜纲. 管理中的数量方法，天津：天津大学出版社，2002
在攻读博士学位期间完成的论文
[1] 吴育华，王初，赵强，CIMS在非制造业的应用分析，中国软科学. 2003;2
[2] 王初，发达国家与发展中国家资本结构的比较，社会科学战线. 2003;10:
[3] 吴育华，王初，城市环境保护相对有效性评价研究，系统工程. 2003;12
[4] 王初，吴育华，咨询公司的价值链分析，科学学与科学技术管理 2003;5
[5] 吴育华，赵强，王初，基于多人合作理论的供应链库存利益分配机制研究，中国管理科学，2002;6:
[6] 滕勇，王初，信息化可持续发展的系统动力学分析，数量经济技术经济研究. 2001，5;
在攻读博士学位期间参与的科研项目
[1] 2000.1－2002.12 国家自然科学基金项目，公理化分配决策理论研究（79970040）
[2] 2003.1－2005.12国家自然科学基金项目，非对称保险市场均衡及其最优保险对策策略研究（70271041）
[3] 2000.1－2002.12博士点基金，分配问题的公理化理论研究
[4] 2002 天同公司投行部人力资源管理系统研究
[5] 2002 商业银行核心竞争力理论与实证研究
[6] 2002 工程项目集成化管理理论与创新研究
[7] 2002－2003 河北省政府网上办公系统
[8] 2002－2003 道勤理财有限公司人力资源管理系统研究
[9] 2003－2004 商业银行治理结构与风险控制研究
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56．Riggs J, Goodman M, Finley R. Miller, T.. A decision support system for predicting project successs, Project Management Journal 1992;23:37-43
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65．R.G. Cooper, S.J. Edgett, E.J. Kleinschmidt, Portfolio Management for New Products, Addison-Wesley, Reading, MA, 1998.
66．Santhanam R, Kyparisis G. A multiple criteria decision model for information system project selection. Computers and Operations Research 1995;22:807-818
67．S.W. Hess, Swinging on the branch of a tree: project selection applications, Interfaces 23 6 1993 5–12.
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69．Apte U, Sankar CS, Thakur M, Turner JE. Reusability-based strategy for development of information systems: implementation experience of a bank. MIS Quarterly 1990;14(4):421-433.
70．Banker RD, Kauffman RJ. Reuse and productivity in integrated computer aided software engineering: an empirical study. MIS Quarterly 1991;15(3):375-401.
71．Muralidhar K, Santhnanm R, Wilson RL. Using the analytic hierarchy process for information system project selection. Information and Management 1990;18(1):87-95.
72．Schneiderjans MJ, Wilson RL. Using the analytic hierarchy process and goal programming for information system project selection. Information and Management 1991;20:333-342.
73．Sanathanam R, Kyparisis GJ. A multiple criteria decision model for information system project selection. Computers Ops Res 1995;22(8):807-818.
74．Santhanam R, Muralidhar K, Schniederjans M. A zero-one goal programming approach for information system project selection. Omega 1989;17(6):583-593.
75．Aaker DA, Tyebjee TT. A model for the selection of interdependent R&D projects. IEEE Transactions on Engineering Management 1978;25(2):30-36.
76．Baker NR. R&D project selection models: an assessment. IEEE Trans Engineering Management 1974;21:165-171.
77．Czajkowski AF, Jones S. Selecting interrelated R&D projects in space technology planning. IEEE Transactions on Engineering Management 1986;33(1):17-24.
78．Fahrni P, Spatig M. An application-oriented guide to R&D project selection and evaluation methods. R&D Management 1990;20(2):155-171.
79．Ringuest JL, Graves SB. The linear multi-objective R&D project selection problem. IEEE Transactions on Engineering Management 1989;36(1):54-57.
80．Badri MA, Davis DL, Davis DF, Hollingsworth J (1998) A multi-objective course scheduling model: combining faculty preferences for courses and times. Computers and Operations Research 25(4):303–316
81．Pal, R., Sinha, K.C., 1998. Optimization approach to highway safety improvement programming. Transportation Research Record 1640, 1–9.
82．STPP, Surface Transportation Policy Project, 1998. Potholes and politics. Washington, DC. Available at http://www.transact.org/Reports/Potholes/title.htm.
83．STPP, Surface Transportation Policy Project, 2000. Changing direction-Federal transportation spending in the 1990s.Washington, DC. Available at http://www.transact.org/Reports/Cd/tea21color.pdf.
84．Visee M., Teghem J. , Pirlot M., Ulungu E.L., 1998. Two phases method and branch and bound to solve bi-objective knapsack problem. Journal of Global Optimization 12, 139–155.
85．D. Pisinger, Budgeting with bounded multiple-choice constraints, in: Proceedings of AIRO'96, Perugia, 17-20 September 1996.
86．S. Rajabi, D.M. Kilgour, K.W. Hipel. Modeling action-interdependence in multiple criteria decision making, European Journal of Operational Research. 1998;110:490-508
87．D.A. Aaker, T.T. Tyebjee. A model for the selection of interdependent R&D projects. IEEE Transitions on Engineering Management 1978;25:30-36
88．G.W. Evans, R. Fairbairn. Selection and scheduling of advanced missions for NASA using 0-1 integer linear programming. Journal of the Operational Research Society. 1989;40:971-981
89． L.F.A. Gomes. Modeling interdependence among urban transportation system alternatives within a multicriteria ranking framework. Journal of Advanced Transportation. 1992;24:77-85
90．G.H. Tzeng, J.Y. Teng. Transportation investment projects selection with fuzzy multiobjectives. Transportation Planning and Technology. 1993;17:91-112
91．Gupta. S.K., Kyparisis J., Ip. C. Project selection and sequencing to maximize the net present value of total return. Management Science. 1992;38:757-752
92．Ibaraki. T. Enumerative approaches to combinational optimization-Part I. Special Issue of Operations Research 1987;10
93．Ibaraki. T. Enumerative approaches to combinational optimization-Part II. Special Issue of
Operations Research 1987;10
94．Ibaraki. T. Resource allocation problems: algorithmic approaches. MIT Press, Cambridge MA, 1988
95．Gupta. S.K., Kyparisis J., Ip. C. Project selection with discounted returns and multiple constraints. European Journal of Operational Research. 1996;94:87-96
96．Merkhofer M. W., Keeney R. L. A multiattribute utility analysis of alternative sites for the disposal of nuclear waste. Risk Analysis,1987;7:173-193
97．Rajabi S., Hipel K.W., Kilgour D.M. Multiple objective water supply planning. Proc. of International Conference on Water Research & Environmental Research: Towards the 21st Century. 1996;2:167-174
98．Fishburn P.C., LaValle I.H. Binary interactions and subset choice. European Journal of Operational Research. 1996;92:182-192
99．Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units.
100．Saaty, T.L The Analytic Hierarchy Process. McGrawHill, New York 1980
101．Roubens, M. Preference relations on actions and criteria in multicriteria decision making. European Journal of Operational Research 1982;10: 51-55.
102．Korhonen, P. Wallenius, J., and Zionts, S. Solving the discrete multiple criteria problem using convex cones. Management Science. 1984;30/11,1336-1345
103．KoKsalan, M., Karwan, M.H. and Zionts, S. An approach for solving discrete alternative multiple criteria problem involving ordinal criteria. Naval Research Logistics Quarterly. 1988;35/6,625-641
104．高天 翟延慧. 特殊多维0－1背包问题的约束简化方法－不等式单约束生成法. 东北师大学报：自然科学版.2002,34(3).-21-26
105．刘红卫 徐凤敏. 二次背包问题的半定规划松驰. 西安电子科技大学学报. 2001,28(5).-638-640,658
106．胡欣 汪红星. 求解多维0-1背包问题的混合遗传算法. 计算机工程与应用. 1999,35(11).-31-33
107．张立昂 李路阳. 多背包问题近似计算的复杂性. 科学通报.1996,41(20).-1896-1898
108．李庆华 李肯立 蒋盛益 张薇. 背包问题的最优并行算法. 软件学报.2003,14(5).-891-896
109．刘西奎 李艳. 背包问题的遗传算法求解. 华中科技大学学报：自然科学版. 2002,30(6).-89-90
110．程泽 寇纪淞. 一种基于免疫思想的混合式遗传算法.天津理工学院学报. 2001,17(4).-16-19
111．刘娜 钟求喜. 求解0－1背包问题的共同进化遗传算法. 计算机科
学.2001,28(9).-102-105
112．夏洁 高金源. 基于禁忌搜索的启发式任务路径规划算法. 控制与决策. 2002,17 (B11).-773-776
113．贺一 刘光远. 禁忌搜索算法求解旅行商问题研究. 西南师范大学学报：自然科学版. 2002,27(3).-341-345
114．邵亮 陈嫦娟. Tabu搜索算法在电话网智能管理中的应用. 软件学报. 2002,13(8). -1705-1709
115．温平川 徐晓东. 并行遗行／模拟退火混合算法及其应用. 计算机科学.2003,30(3).-86-89
116．范晔 周泓. 作业排序模拟退火算法影响因素分析和一种多次淬火模拟退火法. 系统工程理论方法应用.2003,12(1).-72-76
117．谢传泉 何晨. 混沌神经网络模型中的模拟退火策略. 上海交通大学学报. 2003,37(3) -323-326
118．蒋建国 骆正虎. 基于改进型蚁群算求解旅行Agent问题. 模式识别与人工智能.2003,16(1).-6-11
119．覃刚力 杨家本. 自适应调整信息素的蚁群算法. 信息与控制.2002,31(3).-198-201,210
120．郭彤城 慕春棣. 并行遗传算法的新进展. 系统工程理论与实践.2002,22(2).-15-23,41
121．吴育华 付永进. 决策、对策与冲突分析，海口：南方出版社，2001
122．吴育华 杜纲. 管理中的数量方法，天津：天津大学出版社，2002
在攻读博士学位期间完成的论文
[1] 吴育华，王初，赵强，CIMS在非制造业的应用分析，中国软科学. 2003;2
[2] 王初，发达国家与发展中国家资本结构的比较，社会科学战线. 2003;10:
[3] 吴育华，王初，城市环境保护相对有效性评价研究，系统工程. 2003;12
[4] 王初，吴育华，咨询公司的价值链分析，科学学与科学技术管理 2003;5
[5] 吴育华，赵强，王初，基于多人合作理论的供应链库存利益分配机制研究，中国管理科学，2002;6:
[6] 滕勇，王初，信息化可持续发展的系统动力学分析，数量经济技术经济研究. 2001，5;
在攻读博士学位期间参与的科研项目
[1] 2000.1－2002.12 国家自然科学基金项目，公理化分配决策理论研究（79970040）
[2] 2003.1－2005.12国家自然科学基金项目，非对称保险市场均衡及其最优保险对策策略研究（70271041）
[3] 2000.1－2002.12博士点基金，分配问题的公理化理论研究
[4] 2002 天同公司投行部人力资源管理系统研究
[5] 2002 商业银行核心竞争力理论与实证研究
[6] 2002 工程项目集成化管理理论与创新研究
[7] 2002－2003 河北省政府网上办公系统
[8] 2002－2003 道勤理财有限公司人力资源管理系统研究
[9] 2003－2004 商业银行治理结构与风险控制研究