基于多目标优化的矿产资源经济评价模型及其实证研究
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摘要
我国已进入工业化、城市化的中期发展阶段,发展速度之快,令世界瞩目。能源和矿产资源消耗加大,对外依存度加大的趋势,已引起我国国家领导人和有关部门的高度重视,我国政府正大力提倡节约利用,综合利用和循环利用资源,学术界也出现了对国家和地区矿产资源战略问题研究的热潮。矿产资源可持续开发和利用,既关系长远工作,也是紧迫任务。做到合理地可持续地开发和利用矿产资源其首要的任务就是要做好矿产资源经济的评价工作。从上世纪70年代末开始,西方发达国家就把这个工作当作一项国策来考虑,从资金上给予支持,而我国矿产资源经济评价工作比较滞后。
本文重点研究的是将一种新的多目标优化的方法运用到矿产资源的领域,通过比较案例的方式说明了这种方法的先进性。矿产资源经济评价的传统模式是以单目标利益最大化为基础的评价方法,这种方法的评价结果存在一些片面性,它往往注意的是单目标问题。矿产资源经济评价涉及到资源、经济、社会环境以及人口等多个方面,要想对某矿产资源经济作出正确的评价就必须考虑它的多个方面,即多个目标。我们注意到在水资源管理中成功应用的解决多目标优化问题的遗传算法,它不用加权而直接就多目标优化问题通过计算机得出一组解(或称解集),而不是一个解。提供多个解的方式更符合现实决策的需求,能满足用户不同情况下的不同要求,我们力求把它应用到矿产资源经济评价这个领域中来。
本文的研究内容由以下几部分组成：
第一章,在介绍本选题的背景和意义的基础上,综合阐述了国内外关于矿产资源经济评价方法的发展沿革以及多目标优化方法在矿产资源领域的应用；介绍了论文的研究方法和技术路线,论文的框架和创新点。
第二章,阐述了矿产资源经济评价的重要性；确定基于多目标优化的矿产资源经济评价的原则、方法和矿产资源经济评价的重要意义。同时,阐释了几个矿产资源经济评价的基础理论,即矿产资源稀缺性理论；矿产资源价值理论和矿产资源系统性理论。接着介绍了多目标优化的模型、定义和其产生发展的过程；多目标优化的问题直到近20年才得到大力的发展,这是随着遗传算法(GA)、神经网络(ANN)和模糊技术等智能计算技术的发展而发展起来的。这使得多目标优化问题的解决更科学、更高效、更合理、更全面和系统。通过介绍多目标优化方法在矿产资源经济评价中的应用,即层次分析法；灰色系统中的灰色聚类法以及熵技术方法这三种传统方法的具体应用,最终说明多目标优化的遗传算法在矿产资源经济评价中应用的优势。
第三章,介绍了多目标优化的求解方法,即传统的多目标求解方法和现代智能求解方法；在传统的求解方法中介绍了常用的将多目标优化问题转为单目标问题的方法,如：评价函数法、约束法、多目标规划法等；同时介绍了法向约束法、正态边界交点法、基于Pareto前沿的凸多目标法以及间接优化的自组织算法。通过对传统方法的介绍分析了传统方法的不足与缺陷,多目标优化问题的求解需要新的智能计算方法来提高和发展；随后重点介绍了本文选择应用的智能多目标遗传算法,它是借鉴生物进化和自然遗传选择的思想和原理求解实际问题的一种极为有效的方法,根本思想是根据生物中遗传与进化的原理,仿效基因、染色体等物质表达所研究的问题,他有在搜索的过程中将适应值好的个体保存到下一代的特点,会使随机生成的初始解,通过复制、交换、突变等遗传操作不断迭代进化,逐步接近最优解。在遗传算法中我们主要介绍了非支配排序遗传算法(NSGA)和改进的非支配排序遗传算法Ⅱ(NSGA-Ⅱ),它是一种基于Pareto最优概念的遗传算法,该算法就是在基本遗传算法的基础上,对选择再生方法进行改进,将每个个体按照它们的支配与非支配关系进行分层,再做选择操作,从而使得该算法在多目标优化方面可以得到非常满意的结果。
第四章,介绍了基于多目标优化的矿产资源开发模型并进行了实证研究。本章选取了两个经过传统方法计算的矿产资源开发的案例,尝试用非支配排序遗传算法Ⅱ进行一步一步的测试。我们选择GAToolbox作为工具,因为它更易于修改以适应用户的需求。第一个案例为云南某矿业公司两个矿点的总开采期限和开发总利润的双目标优化模型。第二个案例为生产规模和边界品位的决策模型,其涉及到5项经济指标和1项资源利用指标的优化。计算分析结果显示对于多目标矿产资源经济评价问题,两个案例原有的计算方式是将多目标转化为单目标的算法,其仅仅只提供一个解决方案,同时还需要谨慎的制定初始点。而非支配排序遗传算法Ⅱ,其特点是可以提供大量的最优化解决方案并且与起始点的好坏无关,是一个更有效的手段。
第五章,研究了基于多目标优化的矿产资源循环经济评价模型及其实证研究。不同于传统观念的矿产资源经济评价仅涉及到勘察、采矿、选矿、开发利用等方面还应涉及生态环境、社会经济、人口等诸多方面,因此,矿产资源循环经济评价是矿产资源经济评价的新的重要课题。本章阐述了我国矿产资源领域循环经济的发展所面对三个问题：即矿产资源的减量消耗和减少排污量；矿产资源的循环利用；矿产资源所面临的生态环境保护问题。根据这三个问题从社会经济发展指数、能耗指数、排污指数及循环利用指数及其23个相应指标,比较全面的反映了矿业循环经济发展潜力或者支撑能力情况,构建了系统性的矿产资源循环经济评价指标体系,并建立了矿产资源循环经济评价的多目标优化模型,限于数据和相关经济公式的局限性,选取了2006年中国矿业经济数据,运用多目标优化的遗传算法进行计算得到了基于矿业循环经济中污染物排放量的我国矿业的产业结构多个优化方案。最后分析了我国矿业结构的现状,并认为其不是最优的。
第六章,是对全文进行总结并提出建议。
本文的创新之处包括以下几点：
(1)将传统的基于单目标的矿产资源经济评价模型改造为多目标评价模型,对相关矿产经济学的相关模型进行理论拓展。(2)建立新的矿产资源经济评价多目标模型并进行实证分析,力图研究和设计一套适宜于我国矿产资源经济评价的多目标技术方法,为国民经济服务。(3)在多目标优化软件基础上,将计算机遗传计算的方法运用到矿产经济评价的研究中。
Mineral resources are important for mankind's survival and development as well as material foundation for the country's modernization drive. Along with the industrialization and the rapid development of world economy, the resources consumption has also been increased. China has entered the orbit where industrialization and modernization are developing rapidly. The increasing consumption of energy and mineral resources would become an irresistible trend. The shortage of mineral resources, which has attracted great attention of the national authorities, would slow down the country's industrialization and modernization process and could threaten the national security as well. The national government is now vigorously advocating actions of saving, protection, comprehensive and cyclic utilization of resources. A wave of conducting research on strategic issues of national and regional mineral resources has emerged in academic circles. The sustainable development and rational utilization of mineral resources should be undertaken as a pressing task with far-reaching significance. To achieve the task, our priority is to make the economic evaluation of mineral resources. Since the late 1970s, some developed western countries have begun to consider this work as a national policy and to support it with large sums of money. By comparison, our attention was focused on the field of the economic evaluation of mineral resources at a relatively later time.
This thesis focuses on the study of applying the multi-objective optimization method to the field of mineral resources, and to illustrate the advanced nature of this method through case studies. The traditional model of economic evaluation of mineral resources is based on the way of maximizing the interests of single-objective. This method has its limitations and is only feasible in certain aspects, at certain stage and at certain period of time. As the economic evaluation of mineral resources is related to resources, economics, social environment, population and other aspects, we must take various aspects into account, namely, to be of multiple objectives, in order to make a correct assessment of minerals. Meanwhile it is noted that in some disciplines such as water management, they have successfully applied a new method to solve multi-objective problems, which is called Evolutionary algorithm. In respect of multi-objective optimization, this method can get a group of solutions (or a solution set) rather than a sole one directly by the computer without weighting. Providing multiple solutions can serve better real needs of decision-making and can meet specific requirements of customers under different circumstances. Trying to apply the method in the field of economic evaluation of mineral resources is the purpose of the research.
The first part of the thesis introduces the background and significance of the research. Beginning with the influence of the world economy development to the scarcity and non-renewability of mineral resources, this thesis states that countries around the world value mineral resources and it is significant to conduct the economic evaluation of mineral resources. The thesis has reviewed relevant literature researches both at home and abroad by briefly presenting current economic evaluation of mineral resources theories. The fact is that most economic evaluations of mineral resources nowadays are based on single-objective method, or transferring multiple objectives into single objectives via weighting values in their studies. The paper elaborates the method of multi-objective optimization and evolutionary calculation, and its advantage in the application of the economic evaluation of mineral resources. This part also describes research methods and technique routes of the research and puts forward its framework as well as innovations.
The second part, Start with the status quo of China's development and utilization of mineral resources and resource economic evaluation concept, evaluate the scope and content, expounded on the importance of economic evaluation of mineral resources, Determine the multi-objective optimization based on economic evaluation of mineral resources, principles, methods and evaluation of mineral resources of economic importance of the source. That it is with the people's level of knowledge and scientific and technological development and continuous in-depth and complete. At the same time to explain the economic evaluation of mineral resources of several of the basic theory, namely, the theory of scarcity of mineral resources; value theory of mineral resources and mineral resources, systematic theory. Then introduced the multi-objective optimization model, the definition and its formation and development process; Multi-objective optimization problems until the last 20 years was strongly of the development, which along with the genetic algorithm (GA), neural network (ANN) and fuzzy technology, the development of intelligent computing technology to develop. This makes the multi-objective optimization problems more scientific, more efficient,more rational, more comprehensive and systematic. Finally the multi-objective optimization methods in the economic evaluation of mineral resources in the application, through the analytic hierarchy process; gray clustering method in the system as well as the entropy of technical methods of these three traditional methods of comparative analysis of the specific application description, The ultimate explanation of genetic algorithm for multi-objective optimization in the application of economic evaluation of mineral resources advantage.
Part three firstly proposes the concept of multi-objective optimization. In linear and nonlinear programming, the research problems with only one objective function are usually called single-objective optimization. However, the problems met in practical applications often need to optimize by simultaneously using multiple objectives in the given area. This kind of problems are called multi-objective optimization or multi-criteria or multi-attribute optimization, which simultaneously optimize two or more competing objectives on certain condition. Then, the origin and evolution of the multi-objective optimization problems as well as Pareto optimality are expounded. Here, a number of traditional and modern intelligent solutions to multi-objective optimization are also introduced, but the attention is still focused on multi-objective evolutionary algorithm the dissertation applies. This algorithm, which borrows some ideas from biological evolution strategy and natural genetic selection theory, is a comparatively effective solution to practical problems. As to evolutionary algorithm, Non-dominated Sorting Genetic Algorithm (NSGA) and NSGA-Ⅱbased on Pareto optimality are both introduced here. Grounded upon the basic genetic algorithm, NSGA-Ⅱimproves the regeneration methods, classifies individuals according to whether they are dominated or not by each other, and then chooses operation so as to get satisfactory results in optimizing multiple objectives.
Part four In order to study and compare the application of multi-objective optimization method in mineral resources evaluation, two traditional-method based mineral resources exploration cases will be chosen and tested with non-dominated sorting genetic algorithm step by step in this chapter. GAToolbox will be employed because it is easy to modify to meet users' requirement. The first case is the total reservoir life and total profit double objective optimization model of two ore occurrences of a Yunnan mining company. The results yielded by multi-objective method are better than the optimum value generated by step-interactive method in the reference document in both quantity and quality. For one of these results, there is an indicator excelling 5% than the literature value, while another indicator excels 95% than the literature value at the same time. The second case is a decision model of production scale and cut off grade, discussing the optimization of five economic indicators and one resource utilization indicator. By using the multi-objective method, multiunit results have again been generated in this paper, and the six indicators of all these results could excel the one calculated by Hook and Jeeves in the reference document. After analyzing, it is showed that non-dominated sorting genetic algorithm II is an effective tool to multi-objective mineral resources economic evaluation. This algorithm could provide many optimization solutions and is not limited to the quality of starting point, while other present algorithms convert multi-objective to one objective and thus could only provide one solution. Besides, staring points should be cautiously selected.
The fifth part focuses on the sharp increase of resources consumption brought global economy development. The population growth and the large amount consumption of land resource, water resource, energy, and mineral resources have increasingly limited economic development; ecological construction and environment protection situation is increasingly serious. Since the Central Committee of the Communist Party has proposed to develop Circular Economy and construct a resource conserving society under the guidance of scientific development view, a National Circular Economy Conference was held by the central government to discuss the importance and urgency of developing Circular Economy. On the conference, the overall plan and major measures to speed Circular Economy development were suggested that an energy saving and emission reduction society should be developed as a general environment for realizing Circular Economy. To achieve the above goal, mineral resources evaluation should develop from traditional multi-objective open-cycle economic evaluation to complex closing cycle multi-objective economic evaluation, which is a new research subject of mineral resources economic evaluation. Both circular economy and mineral resources have an externality of their own. Environmental pollution brought by the explosion of mineral resources is a typical reflection of non-economical externality. Nevertheless, the premise and the nature of circular economy is cleaner production, requiring extra attention on ecological efficiency in mining. It is also subject to a pursuit of both a maximum utilization of materials and energy and a minimum output of waste residue. However, reuse and recycling of waste have to consume other resources and waste itself constitutes a threat to environment. Multi-objective Optimization Model of Mineral Resources Circular Economy is established then based on China's mining economy data of 2006. The computing results demonstrates the harmonious development between industrial structure and development of circular economy of mining industry in China. The case(case 3) establishes Multi-objective Optimization Model of Mining Industrial Circular Economy, which reflects in all respects the development potential or sustained capability of circular economy of mining industry from the aspects of economic development index of society, energy consumption index, pollution discharge index, recycling index and its 26 corresponding indexes. Because of the limitation of data and corresponding economic formulas, this thesis chooses the economic data of 2006 to optimize the industrial structure of mining industry. The results shows that the proportion of china's industrial structure in 2006 is not optimal. If we could properly increase coal mining and coal washing by 3%-5%, and adjust the proportion of the remaining three sections according to the data shown in the table, it might be able to improve all of the six indexes with the GDP unchanged.
Innovation achieved in this thesis are as follows:
(1) This thesis not only transforms the traditional single-objective economic evaluation model of mineral resources to a multi-objective one, but also does theoretical extension of some models of mining industrial economics. (2) It designs a set of multi-objective technology through research, which is suitable for economic evaluation of mineral resources in China, thus serves the national economy. (3) This thesis applies computer evolutionary algorithm to economic evaluation studies of mining industry on the basis of multi-objective optimization softwares.
本文重点研究的是将一种新的多目标优化的方法运用到矿产资源的领域,通过比较案例的方式说明了这种方法的先进性。矿产资源经济评价的传统模式是以单目标利益最大化为基础的评价方法,这种方法的评价结果存在一些片面性,它往往注意的是单目标问题。矿产资源经济评价涉及到资源、经济、社会环境以及人口等多个方面,要想对某矿产资源经济作出正确的评价就必须考虑它的多个方面,即多个目标。我们注意到在水资源管理中成功应用的解决多目标优化问题的遗传算法,它不用加权而直接就多目标优化问题通过计算机得出一组解(或称解集),而不是一个解。提供多个解的方式更符合现实决策的需求,能满足用户不同情况下的不同要求,我们力求把它应用到矿产资源经济评价这个领域中来。
本文的研究内容由以下几部分组成：
第一章,在介绍本选题的背景和意义的基础上,综合阐述了国内外关于矿产资源经济评价方法的发展沿革以及多目标优化方法在矿产资源领域的应用；介绍了论文的研究方法和技术路线,论文的框架和创新点。
第二章,阐述了矿产资源经济评价的重要性；确定基于多目标优化的矿产资源经济评价的原则、方法和矿产资源经济评价的重要意义。同时,阐释了几个矿产资源经济评价的基础理论,即矿产资源稀缺性理论；矿产资源价值理论和矿产资源系统性理论。接着介绍了多目标优化的模型、定义和其产生发展的过程；多目标优化的问题直到近20年才得到大力的发展,这是随着遗传算法(GA)、神经网络(ANN)和模糊技术等智能计算技术的发展而发展起来的。这使得多目标优化问题的解决更科学、更高效、更合理、更全面和系统。通过介绍多目标优化方法在矿产资源经济评价中的应用,即层次分析法；灰色系统中的灰色聚类法以及熵技术方法这三种传统方法的具体应用,最终说明多目标优化的遗传算法在矿产资源经济评价中应用的优势。
第三章,介绍了多目标优化的求解方法,即传统的多目标求解方法和现代智能求解方法；在传统的求解方法中介绍了常用的将多目标优化问题转为单目标问题的方法,如：评价函数法、约束法、多目标规划法等；同时介绍了法向约束法、正态边界交点法、基于Pareto前沿的凸多目标法以及间接优化的自组织算法。通过对传统方法的介绍分析了传统方法的不足与缺陷,多目标优化问题的求解需要新的智能计算方法来提高和发展；随后重点介绍了本文选择应用的智能多目标遗传算法,它是借鉴生物进化和自然遗传选择的思想和原理求解实际问题的一种极为有效的方法,根本思想是根据生物中遗传与进化的原理,仿效基因、染色体等物质表达所研究的问题,他有在搜索的过程中将适应值好的个体保存到下一代的特点,会使随机生成的初始解,通过复制、交换、突变等遗传操作不断迭代进化,逐步接近最优解。在遗传算法中我们主要介绍了非支配排序遗传算法(NSGA)和改进的非支配排序遗传算法Ⅱ(NSGA-Ⅱ),它是一种基于Pareto最优概念的遗传算法,该算法就是在基本遗传算法的基础上,对选择再生方法进行改进,将每个个体按照它们的支配与非支配关系进行分层,再做选择操作,从而使得该算法在多目标优化方面可以得到非常满意的结果。
第四章,介绍了基于多目标优化的矿产资源开发模型并进行了实证研究。本章选取了两个经过传统方法计算的矿产资源开发的案例,尝试用非支配排序遗传算法Ⅱ进行一步一步的测试。我们选择GAToolbox作为工具,因为它更易于修改以适应用户的需求。第一个案例为云南某矿业公司两个矿点的总开采期限和开发总利润的双目标优化模型。第二个案例为生产规模和边界品位的决策模型,其涉及到5项经济指标和1项资源利用指标的优化。计算分析结果显示对于多目标矿产资源经济评价问题,两个案例原有的计算方式是将多目标转化为单目标的算法,其仅仅只提供一个解决方案,同时还需要谨慎的制定初始点。而非支配排序遗传算法Ⅱ,其特点是可以提供大量的最优化解决方案并且与起始点的好坏无关,是一个更有效的手段。
第五章,研究了基于多目标优化的矿产资源循环经济评价模型及其实证研究。不同于传统观念的矿产资源经济评价仅涉及到勘察、采矿、选矿、开发利用等方面还应涉及生态环境、社会经济、人口等诸多方面,因此,矿产资源循环经济评价是矿产资源经济评价的新的重要课题。本章阐述了我国矿产资源领域循环经济的发展所面对三个问题：即矿产资源的减量消耗和减少排污量；矿产资源的循环利用；矿产资源所面临的生态环境保护问题。根据这三个问题从社会经济发展指数、能耗指数、排污指数及循环利用指数及其23个相应指标,比较全面的反映了矿业循环经济发展潜力或者支撑能力情况,构建了系统性的矿产资源循环经济评价指标体系,并建立了矿产资源循环经济评价的多目标优化模型,限于数据和相关经济公式的局限性,选取了2006年中国矿业经济数据,运用多目标优化的遗传算法进行计算得到了基于矿业循环经济中污染物排放量的我国矿业的产业结构多个优化方案。最后分析了我国矿业结构的现状,并认为其不是最优的。
第六章,是对全文进行总结并提出建议。
本文的创新之处包括以下几点：
(1)将传统的基于单目标的矿产资源经济评价模型改造为多目标评价模型,对相关矿产经济学的相关模型进行理论拓展。(2)建立新的矿产资源经济评价多目标模型并进行实证分析,力图研究和设计一套适宜于我国矿产资源经济评价的多目标技术方法,为国民经济服务。(3)在多目标优化软件基础上,将计算机遗传计算的方法运用到矿产经济评价的研究中。
Mineral resources are important for mankind's survival and development as well as material foundation for the country's modernization drive. Along with the industrialization and the rapid development of world economy, the resources consumption has also been increased. China has entered the orbit where industrialization and modernization are developing rapidly. The increasing consumption of energy and mineral resources would become an irresistible trend. The shortage of mineral resources, which has attracted great attention of the national authorities, would slow down the country's industrialization and modernization process and could threaten the national security as well. The national government is now vigorously advocating actions of saving, protection, comprehensive and cyclic utilization of resources. A wave of conducting research on strategic issues of national and regional mineral resources has emerged in academic circles. The sustainable development and rational utilization of mineral resources should be undertaken as a pressing task with far-reaching significance. To achieve the task, our priority is to make the economic evaluation of mineral resources. Since the late 1970s, some developed western countries have begun to consider this work as a national policy and to support it with large sums of money. By comparison, our attention was focused on the field of the economic evaluation of mineral resources at a relatively later time.
This thesis focuses on the study of applying the multi-objective optimization method to the field of mineral resources, and to illustrate the advanced nature of this method through case studies. The traditional model of economic evaluation of mineral resources is based on the way of maximizing the interests of single-objective. This method has its limitations and is only feasible in certain aspects, at certain stage and at certain period of time. As the economic evaluation of mineral resources is related to resources, economics, social environment, population and other aspects, we must take various aspects into account, namely, to be of multiple objectives, in order to make a correct assessment of minerals. Meanwhile it is noted that in some disciplines such as water management, they have successfully applied a new method to solve multi-objective problems, which is called Evolutionary algorithm. In respect of multi-objective optimization, this method can get a group of solutions (or a solution set) rather than a sole one directly by the computer without weighting. Providing multiple solutions can serve better real needs of decision-making and can meet specific requirements of customers under different circumstances. Trying to apply the method in the field of economic evaluation of mineral resources is the purpose of the research.
The first part of the thesis introduces the background and significance of the research. Beginning with the influence of the world economy development to the scarcity and non-renewability of mineral resources, this thesis states that countries around the world value mineral resources and it is significant to conduct the economic evaluation of mineral resources. The thesis has reviewed relevant literature researches both at home and abroad by briefly presenting current economic evaluation of mineral resources theories. The fact is that most economic evaluations of mineral resources nowadays are based on single-objective method, or transferring multiple objectives into single objectives via weighting values in their studies. The paper elaborates the method of multi-objective optimization and evolutionary calculation, and its advantage in the application of the economic evaluation of mineral resources. This part also describes research methods and technique routes of the research and puts forward its framework as well as innovations.
The second part, Start with the status quo of China's development and utilization of mineral resources and resource economic evaluation concept, evaluate the scope and content, expounded on the importance of economic evaluation of mineral resources, Determine the multi-objective optimization based on economic evaluation of mineral resources, principles, methods and evaluation of mineral resources of economic importance of the source. That it is with the people's level of knowledge and scientific and technological development and continuous in-depth and complete. At the same time to explain the economic evaluation of mineral resources of several of the basic theory, namely, the theory of scarcity of mineral resources; value theory of mineral resources and mineral resources, systematic theory. Then introduced the multi-objective optimization model, the definition and its formation and development process; Multi-objective optimization problems until the last 20 years was strongly of the development, which along with the genetic algorithm (GA), neural network (ANN) and fuzzy technology, the development of intelligent computing technology to develop. This makes the multi-objective optimization problems more scientific, more efficient,more rational, more comprehensive and systematic. Finally the multi-objective optimization methods in the economic evaluation of mineral resources in the application, through the analytic hierarchy process; gray clustering method in the system as well as the entropy of technical methods of these three traditional methods of comparative analysis of the specific application description, The ultimate explanation of genetic algorithm for multi-objective optimization in the application of economic evaluation of mineral resources advantage.
Part three firstly proposes the concept of multi-objective optimization. In linear and nonlinear programming, the research problems with only one objective function are usually called single-objective optimization. However, the problems met in practical applications often need to optimize by simultaneously using multiple objectives in the given area. This kind of problems are called multi-objective optimization or multi-criteria or multi-attribute optimization, which simultaneously optimize two or more competing objectives on certain condition. Then, the origin and evolution of the multi-objective optimization problems as well as Pareto optimality are expounded. Here, a number of traditional and modern intelligent solutions to multi-objective optimization are also introduced, but the attention is still focused on multi-objective evolutionary algorithm the dissertation applies. This algorithm, which borrows some ideas from biological evolution strategy and natural genetic selection theory, is a comparatively effective solution to practical problems. As to evolutionary algorithm, Non-dominated Sorting Genetic Algorithm (NSGA) and NSGA-Ⅱbased on Pareto optimality are both introduced here. Grounded upon the basic genetic algorithm, NSGA-Ⅱimproves the regeneration methods, classifies individuals according to whether they are dominated or not by each other, and then chooses operation so as to get satisfactory results in optimizing multiple objectives.
Part four In order to study and compare the application of multi-objective optimization method in mineral resources evaluation, two traditional-method based mineral resources exploration cases will be chosen and tested with non-dominated sorting genetic algorithm step by step in this chapter. GAToolbox will be employed because it is easy to modify to meet users' requirement. The first case is the total reservoir life and total profit double objective optimization model of two ore occurrences of a Yunnan mining company. The results yielded by multi-objective method are better than the optimum value generated by step-interactive method in the reference document in both quantity and quality. For one of these results, there is an indicator excelling 5% than the literature value, while another indicator excels 95% than the literature value at the same time. The second case is a decision model of production scale and cut off grade, discussing the optimization of five economic indicators and one resource utilization indicator. By using the multi-objective method, multiunit results have again been generated in this paper, and the six indicators of all these results could excel the one calculated by Hook and Jeeves in the reference document. After analyzing, it is showed that non-dominated sorting genetic algorithm II is an effective tool to multi-objective mineral resources economic evaluation. This algorithm could provide many optimization solutions and is not limited to the quality of starting point, while other present algorithms convert multi-objective to one objective and thus could only provide one solution. Besides, staring points should be cautiously selected.
The fifth part focuses on the sharp increase of resources consumption brought global economy development. The population growth and the large amount consumption of land resource, water resource, energy, and mineral resources have increasingly limited economic development; ecological construction and environment protection situation is increasingly serious. Since the Central Committee of the Communist Party has proposed to develop Circular Economy and construct a resource conserving society under the guidance of scientific development view, a National Circular Economy Conference was held by the central government to discuss the importance and urgency of developing Circular Economy. On the conference, the overall plan and major measures to speed Circular Economy development were suggested that an energy saving and emission reduction society should be developed as a general environment for realizing Circular Economy. To achieve the above goal, mineral resources evaluation should develop from traditional multi-objective open-cycle economic evaluation to complex closing cycle multi-objective economic evaluation, which is a new research subject of mineral resources economic evaluation. Both circular economy and mineral resources have an externality of their own. Environmental pollution brought by the explosion of mineral resources is a typical reflection of non-economical externality. Nevertheless, the premise and the nature of circular economy is cleaner production, requiring extra attention on ecological efficiency in mining. It is also subject to a pursuit of both a maximum utilization of materials and energy and a minimum output of waste residue. However, reuse and recycling of waste have to consume other resources and waste itself constitutes a threat to environment. Multi-objective Optimization Model of Mineral Resources Circular Economy is established then based on China's mining economy data of 2006. The computing results demonstrates the harmonious development between industrial structure and development of circular economy of mining industry in China. The case(case 3) establishes Multi-objective Optimization Model of Mining Industrial Circular Economy, which reflects in all respects the development potential or sustained capability of circular economy of mining industry from the aspects of economic development index of society, energy consumption index, pollution discharge index, recycling index and its 26 corresponding indexes. Because of the limitation of data and corresponding economic formulas, this thesis chooses the economic data of 2006 to optimize the industrial structure of mining industry. The results shows that the proportion of china's industrial structure in 2006 is not optimal. If we could properly increase coal mining and coal washing by 3%-5%, and adjust the proportion of the remaining three sections according to the data shown in the table, it might be able to improve all of the six indexes with the GDP unchanged.
Innovation achieved in this thesis are as follows:
(1) This thesis not only transforms the traditional single-objective economic evaluation model of mineral resources to a multi-objective one, but also does theoretical extension of some models of mining industrial economics. (2) It designs a set of multi-objective technology through research, which is suitable for economic evaluation of mineral resources in China, thus serves the national economy. (3) This thesis applies computer evolutionary algorithm to economic evaluation studies of mining industry on the basis of multi-objective optimization softwares.
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