| 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-â…¡based on Pareto optimality are both introduced here. Grounded upon the basic genetic algorithm, NSGA-â…¡improves 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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