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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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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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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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Aircraft Sequencing and Scheduling in Parallel-Point Merge Systems for multiple Parallel Runways

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TRANSPORTATION RESEARCH RECORD 2022年第3期2676卷 108-124页

作者： Donmez, Kadir Cetek, Cem Kaya, Onur Eskisehir Tech Univ Dept Air Traff Control Eskisehir Turkey Eskisehir Tech Univ Dept Ind Engn Eskisehir Turkey

The Point Merge System (PMS) is one of the approaches that offer systematic sequencing in terminal maneuver area (TMA) which was developed at the EUROCONTROL Experimental Centre in 2006. The Parallel-Point Merge System (P-PMS) is used in TMAs with high air traffic density as a combination of two PMSs with opposite directions. However, it is difficult to optimize arrival sequences in such a system because of the additional separation requirements at common points as well as at merge points. Additionally, it is important to operate at maximum efficiency with parallel runway systems when using the runway reassignment process. Reassigning arriving/departing aircraft to a different runway, however, can significantly affect delays and fuel consumption depending on the difference in taxi-in/out times. This effect is overlooked in most aircraft sequencing and scheduling optimization studies with PMS. This study proposes single and multi-objective programming models for a TMA with P-PMS to minimize total fuel consumption, total flight time, and total delay including taxi-in/out times. The models were implemented on the current layout of Istanbul Airport having two PMS with two merge points, three common points, and five parallel runways. The considered traffic scenarios included both dependent and independent runway operations for mixed arrival-departure sequences. The results revealed that arrival-departure sequencing considering taxi-in/out times resulted in shorter delays up to 77.5% and low level of fuel consumption up to 8.7%.

关键词： parallel-point merge system aircraft sequencing and scheduling multiple parallel runways multi-objective programming runway reassignment

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Emergency logistics scheduling with multiple supply-demand points based on grey interval

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Journal of Safety Science and Resilience 2022年第2期3卷 179-188页

作者： Zhiming Ding Xinrun Xu Shan Jiang Jin Yan Yanbo Han University of Chinese Academy of Sciences Beijing100049China Institute of Software Chinese Academy of Sciences Beijing050052China Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data Beijing100124China North China University of Technology Beijing100144China

This study aimed to address the problem of post-disaster emergency material dispatching from multiple supply points to multiple demand *** large-scale natural disasters,it is very important for multiple emergency material supply points to serve as sources of materials for multiple disaster sites and to determine emergency material scheduling solutions ***,the quantity of emergency materials required at each disaster site is *** address this issue,in this study,we developed an emergency material scheduling model with multiple logistics supply points for multiple demand points based on the grey interval *** optimize the proposed multi-supply-point and multi-demand-point emergency material scheduling mode,a multi-objective optimization algorithm based on a genetic algorithm was *** results demonstrate that the multi-objective optimization method can solve the emergency logistics scheduling problem better than the particle swarm optimization multi-objective solution ***,the multi-supply point and multi-demand point emergency material dispatch model and optimization algorithm provides robust support for emergency management system decision-makers when they need to respond quickly to disaster relief activities.

关键词： Emergency logistics scheduling multi-objective programming Disaster relief

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A simulated multi-objective model for flexible job shop transportation scheduling

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ANNALS OF OPERATIONS RESEARCH 2022年第2期311卷 899-920页

作者： Xu, Yiyi Sahnoun, M'hammed Ben Abdelaziz, Fouad Baudry, David CESI LINEACT Lab 80 Rue Edmund Halley Rouen Madrillet Innovat F-76800 St Etienne Du Rouvray France Neoma Business Sch 1 Rue Marchal Juin F-76130 Mont St Aignan France

This paper proposes a new dynamic algorithm based on simulation approach and multi-objective optimization to solve the FJSP with transportation assignment. The objectives considered in scheduling jobs and transportation tasks in a flexible job shop manufacturing system include makespan, robot travel distance, time difference with due date and critical waiting time. The results obtained from the computational experiments have shown that the proposed approach is efficient and competitive.

关键词： Flexible job shop scheduling multi-objective programming Simulation multi-agent systems Transportation

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Solution of multi-objective Linear programming Problems in Intuitionistic Fuzzy Environment 2

Solution of Multi-Objective Linear Programming Problems in I...

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2nd International Conference on Soft Computing for Problem Solving (SocProS)

作者： Bharati, S. K. Nishad, A. K. Singh, S. R. Banaras Hindu Univ Dept Math Varanasi 221005 Uttar Pradesh India

ISBN: (纸本)9788132216025;9788132216018

In the paper, we give a new method for solution of multi-objective linear programming problem in intuitionistic fuzzy environment. The method uses computation of the upper bound of a non-membership function in such way that the upper bound of the non-membership function is always less than the upper bound of the membership function of intuitionistic fuzzy number. Further, we also construct membership and non-membership function to maximize membership function and minimize non-membership function so that we can get a more efficient solution of a probabilistic problem by intuitionistic fuzzy approach. The developed method has been illustrated on a problem, and the result has been compared with existing solutions to show its superiority.

关键词： multi-objective programming Positive ideal solution Intuitionistic fuzzy sets Intuitionistic fuzzy optimization

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