国土整治与生态修复(简称国土整治修复)区域的识别是实施国土整治修复的前提,土地资源优化格局的落实是土地资源优化配置的关键。立足于双重需求,本文提出了一种基于土地资源优化配置的国土整治修复潜在区域识别策略,并以黄河流域为研究...国土整治与生态修复(简称国土整治修复)区域的识别是实施国土整治修复的前提,土地资源优化格局的落实是土地资源优化配置的关键。立足于双重需求,本文提出了一种基于土地资源优化配置的国土整治修复潜在区域识别策略,并以黄河流域为研究区,借助Multi-Objective Linear Programming(MOLP)模型与Patch-generating Land Use Simulating(PLUS)模型,有效衔接了“理想状态”的土地资源优化格局与“实际行动”的国土整治修复。结果发现:①不同土地利用类型的发展概率具有显著差异,且同一土地类型发展概率的空间分异特征明显。②惯性发展格局下,流域建设用地将大规模扩张,草地缩减与耕地流失严峻;优化发展格局下,建设用地蔓延、耕地流失与草地面积缩减均得以控制,且实现了生态及经济效益的稳步提升。③识别出农地整理区、生态涵养区与后备资源区(Ⅰ型、Ⅱ型)4种非转型类潜在区域和农地开发区、生态退耕区、生态保育区和生态维护区4种转型类区域;相较于非转型类区域,转型类区域需要借助更多的国土整治与生态修复干预措施。建设用地的无序蔓延会导致大量草地及耕地损失,土地资源的优化配置能有效缓解城市蔓延与保护(半)自然空间,基于此识别出不同国土整治修复区域并采取差异化的措施不仅能保障受威胁的粮食与生态安全,还可促进流域生态及经济效益提升、生态系统恢复与土地利用稳定性提升。本文提出的方法不仅为国土整治修复区域划定提供了科学依据,同时为土地资源优化格局的落实提供了参考路径。展开更多
In this paper, a modified method to find the efficient solutions of multi-objective linear fractional programming (MOLFP) problems is presented. While some of the previously proposed methods provide only one efficient...In this paper, a modified method to find the efficient solutions of multi-objective linear fractional programming (MOLFP) problems is presented. While some of the previously proposed methods provide only one efficient solution to the MOLFP problem, this modified method provides multiple efficient solutions to the problem. As a result, it provides the decision makers flexibility to choose a better option from alternatives according to their financial position and their level of satisfaction of objectives. A numerical example is provided to illustrate the modified method and also a real life oriented production problem is modeled and solved.展开更多
Environmental and social problems caused by overfertilization,excessive pesticides,and encroachment on farmland are increasingly serious in agricultural settings,especially in suburban agricultural areas and highly in...Environmental and social problems caused by overfertilization,excessive pesticides,and encroachment on farmland are increasingly serious in agricultural settings,especially in suburban agricultural areas and highly intensive agricultural areas.Hence,modern agriculture not only pursues economic benefits,but it also pays more attention to ecological functions and social stability.This paper proposes a set of methods which are designed to realize optimal agricultural benefits and sustainable development by scientifically adjusting the land use structure.Taking Changsha County in South Central China as a case study,this paper first built an index system and adopted the information entropy-TOPSIS method to assess the economic,social,and ecological benefits of agricultural land use.Next,a coupled coordination model and an obstacle model were chosen to diagnose those factors that remained as obstacles to achieving the sustainable and coordinated development of the benefits of agricultural land use.Finally,based on the analysis of the changes in the benefits and obstacles over time,socio-economic and ecological constraints were established,and the multi-objective linear programming method(MOLP)was used to determine the comprehensive benefits and optimal land use structure.The results indicate that:(1)The agricultural benefits were stably increasing from 0.20 in 1996 to 0.79 in 2016.(2)The economic benefit index is no longer the main obstacle,while the social benefit index,which includes components such as the food security index,has become the principal influencing factor.(3)The optimal land use structure and comprehensive benefits were presented by taking into consideration the economic development,environmental protection,and social needs.This study emphasizes economic development,but it also seeks coordinated development with comprehensive benefits.The results of the study could provide scientific recommendations for optimizing the agricultural land use spatial patterns and sustainable land use.展开更多
This paper is concerned with the resource allocation problem based on data envelopment analysis （DEA） which is generally found in practice such as in public services and in production process. In management context,...This paper is concerned with the resource allocation problem based on data envelopment analysis （DEA） which is generally found in practice such as in public services and in production process. In management context, the resource allocation has to achieve the effective-efficient-equality aim and tries to balance the different desires of two management layers： central manager and each sector. In mathematical programming context, to solve the resource allocation asks for introducing many optimization techniques such as multiple-objective programming and goal programming. We construct an algorithm framework by using comprehensive DEA tools including CCR, BCC models, inverse DEA model, the most compromising common weights analysis model, and extra resource allocation algorithm. Returns to scale characteristic is put major place for analyzing DMUs＇ scale economies and used to select DMU candidates before resource allocation. By combining extra resource allocation algorithm with scale economies target, we propose a resource allocation solution, which can achieve the effective-efficient-equality target and also provide information for future resource allocation. Many numerical examples are discussed in this paper, which also verify our work.展开更多
文摘国土整治与生态修复(简称国土整治修复)区域的识别是实施国土整治修复的前提,土地资源优化格局的落实是土地资源优化配置的关键。立足于双重需求,本文提出了一种基于土地资源优化配置的国土整治修复潜在区域识别策略,并以黄河流域为研究区,借助Multi-Objective Linear Programming(MOLP)模型与Patch-generating Land Use Simulating(PLUS)模型,有效衔接了“理想状态”的土地资源优化格局与“实际行动”的国土整治修复。结果发现:①不同土地利用类型的发展概率具有显著差异,且同一土地类型发展概率的空间分异特征明显。②惯性发展格局下,流域建设用地将大规模扩张,草地缩减与耕地流失严峻;优化发展格局下,建设用地蔓延、耕地流失与草地面积缩减均得以控制,且实现了生态及经济效益的稳步提升。③识别出农地整理区、生态涵养区与后备资源区(Ⅰ型、Ⅱ型)4种非转型类潜在区域和农地开发区、生态退耕区、生态保育区和生态维护区4种转型类区域;相较于非转型类区域,转型类区域需要借助更多的国土整治与生态修复干预措施。建设用地的无序蔓延会导致大量草地及耕地损失,土地资源的优化配置能有效缓解城市蔓延与保护(半)自然空间,基于此识别出不同国土整治修复区域并采取差异化的措施不仅能保障受威胁的粮食与生态安全,还可促进流域生态及经济效益提升、生态系统恢复与土地利用稳定性提升。本文提出的方法不仅为国土整治修复区域划定提供了科学依据,同时为土地资源优化格局的落实提供了参考路径。
文摘In this paper, a modified method to find the efficient solutions of multi-objective linear fractional programming (MOLFP) problems is presented. While some of the previously proposed methods provide only one efficient solution to the MOLFP problem, this modified method provides multiple efficient solutions to the problem. As a result, it provides the decision makers flexibility to choose a better option from alternatives according to their financial position and their level of satisfaction of objectives. A numerical example is provided to illustrate the modified method and also a real life oriented production problem is modeled and solved.
基金The National Natural Science Foundation of China(41801216)The Fundamental Research Funds for the Central Universities of China(2018B20914)。
文摘Environmental and social problems caused by overfertilization,excessive pesticides,and encroachment on farmland are increasingly serious in agricultural settings,especially in suburban agricultural areas and highly intensive agricultural areas.Hence,modern agriculture not only pursues economic benefits,but it also pays more attention to ecological functions and social stability.This paper proposes a set of methods which are designed to realize optimal agricultural benefits and sustainable development by scientifically adjusting the land use structure.Taking Changsha County in South Central China as a case study,this paper first built an index system and adopted the information entropy-TOPSIS method to assess the economic,social,and ecological benefits of agricultural land use.Next,a coupled coordination model and an obstacle model were chosen to diagnose those factors that remained as obstacles to achieving the sustainable and coordinated development of the benefits of agricultural land use.Finally,based on the analysis of the changes in the benefits and obstacles over time,socio-economic and ecological constraints were established,and the multi-objective linear programming method(MOLP)was used to determine the comprehensive benefits and optimal land use structure.The results indicate that:(1)The agricultural benefits were stably increasing from 0.20 in 1996 to 0.79 in 2016.(2)The economic benefit index is no longer the main obstacle,while the social benefit index,which includes components such as the food security index,has become the principal influencing factor.(3)The optimal land use structure and comprehensive benefits were presented by taking into consideration the economic development,environmental protection,and social needs.This study emphasizes economic development,but it also seeks coordinated development with comprehensive benefits.The results of the study could provide scientific recommendations for optimizing the agricultural land use spatial patterns and sustainable land use.
基金This research is supported by 973 Program under Grant No.2006CB701306
文摘This paper is concerned with the resource allocation problem based on data envelopment analysis （DEA） which is generally found in practice such as in public services and in production process. In management context, the resource allocation has to achieve the effective-efficient-equality aim and tries to balance the different desires of two management layers： central manager and each sector. In mathematical programming context, to solve the resource allocation asks for introducing many optimization techniques such as multiple-objective programming and goal programming. We construct an algorithm framework by using comprehensive DEA tools including CCR, BCC models, inverse DEA model, the most compromising common weights analysis model, and extra resource allocation algorithm. Returns to scale characteristic is put major place for analyzing DMUs＇ scale economies and used to select DMU candidates before resource allocation. By combining extra resource allocation algorithm with scale economies target, we propose a resource allocation solution, which can achieve the effective-efficient-equality target and also provide information for future resource allocation. Many numerical examples are discussed in this paper, which also verify our work.
