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A multi-objective programming approach, integrated into the TOPSIS method, in order to optimize product design;in three-dimensional concurrent engineering

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COMPUTERS & INDUSTRIAL ENGINEERING 2013年第4期64卷 875-885页

作者： Shidpour, H. Shahrokhi, M. Bernard, A. Univ Kurdistan Dept Engn Sanandaj Iran Ecole Cent Nantes F-44321 Nantes 3 France

This paper proposes a new method to address a three-dimensional concurrent engineering (3D-CE) approach. It uses a multi-objective Linear programming (MOLP) model integrated to the TOPSIS method in order to determine the best configuration product design, assembly process and suppliers of components. This method is able to involve various supply chain strategies by considering qualitative and quantitative criteria in the early stages of the new product development (NPD) process. It also applies the Fuzzy Analytic Hierarchy Process (FAHP) method to determine the relative importance of criteria defined to evaluate configurations of design alternatives, assembly processes and suppliers of components. A sensitivity analysis from different parameters in the model that affect the selection of the best design alternative is performed by creating a computer program using visual studio. A numerical example is used to demonstrate method efficacy and finally, the paper suggests some areas for future research. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： New product development TOPSIS 3D-CE Qualitative and quantitative parameters multi-objective programming FAHP

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Development of a New Municipal Solid Waste Management System: multi-objective programming for a Merged Metropolis

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ENVIRONMENTAL ENGINEERING SCIENCE 2013年第4期30卷 153-160页

作者： Wu, Edward Ming-Yang Tsai, Chia-Cheng Lin, Chitsan Kuo, Shu-Lung Kang, Zhi-Bo I Shou Univ Dept Civil & Ecol Engn Kaohsiung Taiwan Natl Kaohsiung Marine Univ Dept Marine Environm Engn Kaohsiung 811 Taiwan Natl Univ Kaohsiung Gen Educ Ctr Kaohsiung Taiwan

On December 25, 2010, two administrative regions with entirely different administrative status, resources, and areas of development, Kaohsiung City and Kaohsiung County, were required by a long-term national land reform program in Taiwan to merge into one administrative entity. A new plan for managing solid wastes had to be quickly implemented to provide services of equal quality to all residents. The government of the new administrative region is required to initiate a new plan at the top level to provide a platform for planning sublevel solid waste collection and disposal systems. To address the issue, this study used an urban planning approach and multi-objective mathematical programming to reconcile conflicting objectives within the system, which must be built and maintained at minimum cost and provide maximum equity. Because the second objective of maximum equity is difficult to express quantitatively, this study initiated an indicator for this variable, that is, to minimize the total metric ton-kilometers of waste being transported. Furthermore, a constraint method was introduced to simplify the two objectives into a single objective function. Additionally, this model pioneered the inclusion of time as a variable. This made possible a time-dependent dynamic annual solution for each year of the 10-year study period. Hence, the model reflected the actual solid waste complexity in the newly merged region and provided valuable information for top-down planning of future subsystems projects.

关键词： cost minimization deterministic status modeling of equity multi-objective programming municipal solid waste management superior plan

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Optimizing the industrial structure of a watershed in association with economic-environmental consideration: an inexact fuzzy multi-objective programming model

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JOURNAL OF CLEANER PRODUCTION 2013年 42卷 116-131页

作者： Zhou, M. Chen, Q. Cai, Y. L. Peking Univ Coll Urban & Environm Sci Beijing 100871 Peoples R China Qinghai Normal Univ Coll Life & Geog Sci Xining 810008 Qinghai Peoples R China

An inexact fuzzy multi-objective programming model (IFMOP) is developed in this study for dealing with industrial structure optimization problems under uncertainty. The IFMOP model is formulated based on integration of an inexact linear programming (ILP), fuzzy flexible optimization (FFO), and multi-objective programming (MOP). It improves upon the existing industrial structure optimization model with advantages in uncertainty reflection, model coupling, data availability and computational requirement. The model can deal with uncertainties expressed as discrete intervals and fuzzy sets. Therefore, it can effectively reflect dynamic, interactive complex, and uncertain characteristics of industrial system without unrealistic simplification. Moreover, the model can be used for supporting temporal and spatial optimization of industrial structure under a variety of environmental and socio-economic conditions. The developed model is first applied to a real case of planning industrial structure of South Four Lake watershed in Shandong province, China. Results demonstrated that the model could help decision makers generate stable and balanced industrial structure patterns, gain in-depth insights into effects of the uncertainties, and analyze trade-offs among economical objective, environmental protection and social demand. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Inexact linear programming Fuzzy flexible programming multi-objective programming Hybrid uncertain model Industrial structure optimization

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A bi-objective mathematical model for an unrelated parallel machine scheduling problem with job-splitting

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2022年第4期37卷 2293-2307页

作者： Sarac, Tugba Tutumlu, Busra Eskisehir Osmangazi Univ Fac Engn & Architecture Ind Enginering Dept TR-26480 Eskisehir Turkey Kutahya Dumlupinar Univ Fac Engn Ind Enginering Deparment TR-43100 Kutahya Turkey

Studies dealing with parallel machine scheduling problems generally assume that jobs are not split. However, splitting of jobs can offer opportunities such as delivering the jobs on time or evenly distributing the jobs to the machines. In this study, two different multi-objective mathematical models are proposed for the unrelated parallel machine scheduling problem without and with job-splitting. The first model is for the unrelated parallel machine scheduling problem without job-splitting and it was developed based on the model proposed by Sarac and Tutumlu [1]. In the second model, in which the jobs can split, besides the machines to which the jobs will be assigned and their order, it is also determined how the jobs will split and in which ratios the jobs will be processed on which machines. The objectives of both models are to minimize the completion time of the last job and the number of machines to be used. multi-objective models were transformed into a single-objective structure with the epsilon constraint method. Randomly generated test problems were solved with the proposed models using the GAMS/Cplex solver, and the results were compared. Considering the problems for which the optimum solution is obtained, the first model found a solution in an average of 85% less time than the model in the literature [1], and the second model shortens the completion time of the last job in an average of 14%. In addition, a mathematical heuristic algorithm is proposed for solving large-size problems.

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Improving the AquaCrop model to achieve direct simulation of evapotranspiration under nitrogen stress and joint simulation-optimization of irrigation and fertilizer schedules

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AGRICULTURAL WATER MANAGEMENT 2022年第0期266卷

作者： Wu, Hui Yue, Qiong Guo, Ping Xu, Xiaoyu Huang, Xi China Agr Univ Ctr Agr Water Res China Beijing 100083 Peoples R China Res Stn Efficient Water Use Oasis Agr Wuwei Gansu Natl Field Sci Observat Wuwei 733000 Gansu Peoples R China

Water and fertilizer management strategy profoundly influences crop yield, water and nitrogen use efficiency. In this study, a framework for joint simulation-optimization of irrigation and fertilizer schedules (JSOIFS) was established by coupling the improved AquaCrop model, W*N-Jensen model and multi-objective programming. Firstly, the AquaCrop model was modified to simulate evapotranspiration (ET) under nitrogen stress through introducing the concept of shoot actual, critical and minimal nitrogen concentration. The accuracy and applicability of the improved AquaCrop model to simulate ET were verified, taking seed maize of Shiyanghe River Basin as a case. On the basis, an optimization model with the objective of maximum yield calculated by W*NJensen model and water use efficiency was developed under the scenarios of different levels of available water and nitrogen, and initial soil mineral nitrogen content. Results showed that the improved model can simulate canopy cover (CC) and ET well with and without water stress. Meanwhile, the precision for CC, biomass, ET and yield of seed maize can be guaranteed when water and nitrogen stress coexist. It indicated that the improved model can be used for irrigation and fertilizer management. The optimal irrigation and fertilizer schedules pointed out that the irrigation and nitrogen application, and initial soil mineral nitrogen all have significant effects on yield. In low fertility soils, irrigation should be concentrated during tasseling stage and fertilization is as critical as irrigation. Conversely, in high fertility soils, irrigation should be dispersed throughout the growth period. Water and nitrogen use efficiency have been promoted compared with the status quo. The recommended water and nitrogen application for seed maize are 150-200 mm and 100-150 kg N/ha, respectively, in study area with the mean soil mineral nitrogen of 182 kg N/ha. The improvement of ET simulation performance of AquaCrop model under simultaneou

关键词： Optimization Irrigation and fertilizer management AquaCrop multi-objective programming

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Fuzzy goal programming technique for multi-objective indefinite quadratic bilevel programming problem

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ARCHIVES OF CONTROL SCIENCES 2020年第4期30卷 683-699页

作者： Arora, R. Gupta, K. Univ Delhi Dept Math Keshav Mahavidyalaya Delhi India Univ Delhi Kirori Mal Coll Dept Math Delhi India

Bilevel programming problem is a non-convex two stage decision making process in which the constraint region of upper level is determined by the lower level problem. In this paper, a multi-objective indefinite quadratic bilevel programming problem (MOIQBP) is presented. The defined problem (MOIQBP) has multi-objective functions at both the levels. The followers are independent at the lower level. A fuzzy goal programming methodology is employed which minimizes the sum of the negative deviational variables of both the levels to obtain highest membership value of each of the fuzzy goal. The membership function for the objective functions at each level is defined. As these membership functions are quadratic they are linearized by Taylor series approximation. The membership function for the decision variables at both levels is also determined. The individual optimal solution of objective functions at each level is used for formulating an integrated pay-off matrix. The aspiration levels for the decision makers are ascertained from this matrix. An algorithm is developed to obtain a compromise optimal solution for (MOIQBP). A numerical example is exhibited to evince the algorithm. The computing software LINGO 17.0 has been used for solving this problem.

关键词： bilevel programming indefinite quadratic programming multi-objective programming pay-off matrix Taylor series approximation LINGO 17.0

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SDG-oriented multi-scenario sustainable land-use simulation under the background of urban expansion

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2022年第48期29卷 72797-72818页

作者： Zhou, Min Ma, Yuxiang Tu, Jiating Wang, Mengcheng Huazhong Univ Sci & Technol Coll Publ Adm 1037 Luoyu Rd Wuhan Peoples R China

With the continuous improvement of urbanization level and the continuous expansion of city scale, there are some unreasonable land development and utilization problems, which will make the contradiction between people and land more prominent and the risk of ecological environment deterioration more serious. It hinders the sustainable land use (SLU) and then affects the realization of regional Sustainable Development Goals (SDGs). SDGs have become a programmatic document for all countries in the world to implement sustainable development. It provides a guideline and direction for the sustainable urban expansion. The sustainable urban expansion promotes the realization of SDGs worldwide. By combining the SDGs with the urban SLU, this paper obtains the optimized future land-use demand of the multi-scenario city and the urban expansion simulation scenario to the SDGs under the multi-scenario through the uncertain mathematical model (MIFCCP) and the spatial simulation model (PLUS). We find that firstly, the net profit of land use (LNB) reaches the highest value under the economic development scenario (ED), when the probability of environmental constraint violation p = 0.01 and p = 0.15, LNB = [2625.48, 3244.98] x 10(9) CNY, and [2646.95, 3271.51] x 10(9) CNY. Ecosystem service value (ESV) reached the highest value under the sustainable development scenario (SD), when p = 0.01 and p = 0.15, ESV = [75.34, 93.12] x 10(9) CNY, and [72.62, 95.56] x 10(9) CNY. The net carbon emissions from land use (LNC) reached the minimum value in SD scenario, and when p = 0.01 and p = 0.15, the LNC reached [57.46, 71.02] x 10(6) ton and [56.12, 76.04] x 10(6) ton. Secondly, the contribution degree of 15 driving factors to the change of local types is excavated, among which, the driving factors of traffic stations have the highest contribution degree to the change of construction land and cultivated land, and the third-class roads have the highest contribution degree to the change of wetland

关键词： Sustainable land use SDGs multi-objective programming Uncertain model Patch-generating simulation Land use simulation

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A credibility-based interval multi-objective crop area planning model for agricultural and ecological management

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AGRICULTURAL WATER MANAGEMENT 2022年第0期269卷

作者： Chen, Junxu Zhang, Chenglong Guo, Ping China Agr Univ Coll Water Resource & Civil Engn Beijing 100083 Peoples R China Natl Observ & Res Stn Oasis Agr Ecosyst Wuwei Gansu Peoples R China

This study presents a credibility-based interval multi-objective crop area planning model for agricultural and ecological management under uncertainty. The model is developed through the integrations of interval multi-objective programming and fuzzy credibility-constrained programming by considering economic and ecological benefits of the study system, and dealing with interval and fuzzy uncertainties. It focuses on crop area optimization with the interval objective function of maximizing the system benefits, maximizing the watershed area, and fractional interval objective function of maximizing the land productivity (i.e., system benefits per unit area). Additionally, the relationship between watershed area and ecological discharge is expressed as interval linear function, which is estimated by using interval regression analysis method. Then, the model is applied to a case study in Minqin County in the lower reaches of Shiyang River Basin for crop area optimization in view of the increasing shortage of water resources and the competition between agricultural and ecological water use. Optimal solutions for different scenarios can be generated based on fuzzy credibility constraints when the pre-defined credibility levels are set as 0.6, 0.7 and 0.8, 0.9, respectively. The results show that the crop area optimization model can better balance the regional agricultural and ecological benefits while ensuring grain production and promoting water saving. Moreover, a higher level of credibility corresponds to a lower system benefit but a larger watershed area. When credibility level is raised from 0.6 to 0.9, the upper bounds of system benefits are decreased from 13.87x10(8) Yuan to 13.81x10(8) Yuan whereas the watershed area is increased from 41.01 km(2) to 42.12 km(2). These various optimal results can help decision makers weigh system benefits and constraint-violation risks. Therefore, the results of the model can provide decision-making basis for the crop area optimizat

关键词： Interval multi-objective programming Credibility Ecological management Crop area planning Uncertainty

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Portfolio optimization using elliptic entropy and semi-entropy of coherent fuzzy numbers

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INFORMATION SCIENCES 2022年 614卷 240-262页

作者： Gupta, Pankaj Univ Delhi Dept Operat Res Delhi 110007 India

This paper explores the elliptic entropy and the elliptic semi-entropy of a coherent fuzzy number and discusses several of their properties. We propose a methodology that incorporates the adaptive index, k, of the coherent fuzzy number representing an individual investor's stock market assessment (pessimistic, optimistic, or neutral). We combine the adaptive index with the elliptic entropy and semi-entropy to obtain risk measures incorporating investor attitude. We use the proposed risk measures in a portfolio optimization problem that uses coherent fuzzy numbers to model the asset returns. The optimization models are solved using a genetic algorithm. We apply the proposed methodology to a large-scale case study involving 100 assets to demonstrate its effectiveness. The realworld performance of the proposed approach is illustrated using an out-of-sample analysis. Based on the results we obtained, we discuss the advantages and disadvantages of elliptic entropy and semi-entropy. Finally, we compare the proposed methodology with other approaches in the literature and demonstrate its superiority. (c) 2022 Elsevier Inc. All rights reserved.

关键词： Fuzzy portfolio optimization Credibility theory Coherent fuzzy numbers Elliptic entropy Elliptic semi-entropy multi-objective programming Genetic algorithm

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Economic-Environment-Energy (3E) objective-driven integrated municipal waste management under deep complexities - A novel multi-objective approach

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SUSTAINABLE CITIES AND SOCIETY 2022年第0期87卷

作者： Liang, Xiaolin Ji, Ling Xie, Yulei Huang, Guohe Beijing Univ Technol Sch Econ & Management Beijing 100124 Peoples R China Guangdong Univ Technol Inst Environm & Ecol Engn Guangzhou 510006 Guangdong Peoples R China Univ Regina Inst Energy Environm & Sustainable Communities Regina SK S4S 0A2 Canada

Waste-to-energy technologies compatible with recycling are promising solutions for sustainable municipal waste management from both economic and environmental perspectives. This study focuses on the economic -environment-energy (3E) objective-driven integrated waste management optimization problems under deep complexities. A novel multi-objective programming model is developed to assist the optimal decision-making with the consideration of system profit, greenhouse gas emission, and energy recovery simultaneously. Be-sides, it advances existing optimization methods by incorporating interval-valued fuzzy numbers to tackle the ambiguity and the essential fuzziness in experts' judgment. It was verified by a case study from an urban district of Beijing, China. The optimum waste treatment facility planning and waste stream allocation strategies with multi-objective tradeoffs were obtained to support decision-making considering different preferences of impor-tance ranking. In general, incineration and anaerobic digestion would be the main technologies for waste disposal in the study area. Recycling would be greatly encouraged when pursuing more economic profits and greenhouse gas emission reduction. With withdrawing the subsidy in the future, the investment in anaerobic digestion would become less attractive. Meanwhile, the landfill with gas recovery would even become economically infeasible if there is no further reduction in cost. In addition, waste source separation is also a crucial factor for successful integrated waste management. It is suggested that a proper government subsidy and public participation in waste source separation would guarantee the sustainable development of the integrated waste management system.

关键词： Waste-to-energy Waste management Interval-valued fuzzy parameters multi-objective programming

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