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Sustainable supplier selection and order allocation: An integrated delphi method, fuzzy TOPSIS, and multi-objective programming model

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SCIENTIA IRANICA 2019年第4期26卷 2524-2540页

作者： Rabieh, M. Rafsanjani, A. Fadaei Babaei, L. Esmaeili, M. Shahid Beheshti Univ Fac Management & Accounting Tehran Iran Allameh Tabataba1 Univ Fac Management & Accounting Ind Management Tehran Iran

The purpose of the current study is to select suppliers and determine their order allocation in a way that the performance of the sustainability of the supply process gets optimized on the whole. In this research, after reviewing the literature and investigating the supply chain of the case study (Iran Khodro's supply chain) through Delphi method, a set of evaluation criteria related to the performance of the suppliers in economic, social, and environmental terms was identified. In the next stage, by using the identified criteria, the multi-objective mathematical integer programming was presented to solve the problems of supplier selection and order allocation. The suggested mathematical programming in this research is designed to be multi-product, single-period, and multiple sourcing. Fuzzy TOPSIS method is applied to calculate the qualitative parameters that are used in the suggested mathematical programming. Ultimately, the mathematical model suggested in the research is solved by two methods, i.e., epsilon constraint method and weighted sum method. Moreover, the Total Value of Sustainable Purchasing (TVSP) is calculated for both cases. The comparison of these two methods indicates that, in this research, the results of the weighted sum method are more efficient than those of the epsilon constraint method. (C) 2019 Sharif University of Technology. All rights reserved.

关键词： Sustainable supplier selection Order allocation Fuzzy TOPSIS multi-objective programming Epsilon constraint method Weighted sum method

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Isolated efficiency in nonsmooth semi-infinite multi-objective programming

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OPTIMIZATION 2018年第11期67卷 1923-1947页

作者： Rahimi, Morteza Soleimani-damaneh, Majid Univ Tehran Coll Sci Sch Math Stat & Comp Sci Tehran Iran

In this paper, isolated efficient solutions of a given nonsmooth multi-objective Semi-Infinite programming problem (MOSIP) are studied. Two new Data Qualifications (DQs) are introduced and it is shown that these DQs are, to a large extent, weaker than already known Constraint Qualifications (CQs). The relationships between isolated efficiency and some relevant notions existing in the literature, including robustness, are established. Various necessary and sufficient conditions for characterizing isolated efficient solutions of a general problem are derived. It is done invoking the tangent cones, the normal cones, the generalized directional derivatives, and some gap functions. Using these characterizations, the (strongly) perturbed Karush-Kuhn-Tucker (KKT) optimality conditions for MOSIP are analyzed. Furthermore, it is shown that each isolated efficient solution is a Geoffrion properly efficient solution under appropriate assumptions. Moreover, Kuhn-Tucker (KT) and Klinger properly efficient solutions for a nonsmooth MOSIP are defined and it is proved that each isolated efficient solution is a KT properly efficient solution in general, and a Klinger properly efficient solution under a DQ. Finally, in the last section, the largest isolated efficiency constant for a given isolated efficient solution is determined.

关键词： multi-objective programming semi-infinite programming nonsmooth optimization isolated efficient solution robustness gap function

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A multi-objective programming Method Based on Relative Deviation 8

A Multi-objective Programming Method Based on Relative Devia...

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8th International Conference on Logistics, Informatics and Service Sciences (LISS)

作者： Li, Fachao Feng, Kaixin Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang Hebei Peoples R China

ISBN: (纸本)9781538669655

multi-objective programming, as an effective mathematical model for dealing with multiple objectives, is widely used in the fields of complex system optimization, management decision analysis and artificial intelligence. This paper first analyzes the characteristics and deficiencies of the multi-objective planning model based on priority factors, and proposes a multi-objective planning method based on relative deviations. It mainly introduces the relative deviation to describe the degree of deviation from the target value and reflect the satisfactory state of the decision results. It establishes a planning model in which each objective is at the same level, and analyzes the effectiveness of the method in conjunction with a specific case. The comprehensive analysis and the corresponding conclusions show that the solution model established not only ensures the existence of the solution, but also guarantees the reliability of the decision-making result. It has strong explanatory and operability, and to a certain extent, enriches the existing fuzzy decision-making method.

关键词： relative deviation multi-objective programming linear target programming priority factor

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Fuzzy rough bi-level multi-objective nonlinear programming problems

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ALEXANDRIA ENGINEERING JOURNAL 2019年第4期58卷 1471-1482页

作者： Elsisy, M. A. El Sayed, M. A. Benha Univ Fac Engn Dept Basic Engn Sci Elqalyoubia Egypt

Fuzzy rough bi-level multi-objective nonlinear programming problem (FRBMNPP) moved toward becoming rise normally in various real applications. In this article we develop bi-level multi-objective nonlinear programming problem (BMNPP), in which the objective functions have fuzzy nature and the constraints represented as a rough set. The fuzzy objective functions converted into deterministic ones by utilizing the alpha-cut methodology. Thus the FRBMNPP become a rough BMNPP which is transformed into two problems corresponding to the upper and lower approximation models. The Karush-Kuhn-Tucker (KKT) method and two models of technique of order preferences by similarity to ideal solution (TOPSIS) approach are developed to solve such problem. At last, applicability and efficiency of the two TOPSIS models and KKT method, suggested in this study, are presented through an algorithm and a numerical illustration. (C) 2019 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University.

关键词： Bi-level optimization multi-objective programming Rough set Fuzzy sets TOPSIS Karush-Kuhn-Tucker (KKT) method

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Selecting the best route in a theme park through multi-objective programming

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TOURISM GEOGRAPHIES 2018年第5期20卷 791-809页

作者： Rodriguez-Diaz, Beatriz Ignacio Pulido-Fernandez, Juan Univ Malaga Dept Appl Econ Math Malaga Spain Univ Jaen Dept Econ Lab Anal & Innovat Tourism Jaen Spain

The theme park industry has grown intensely in recent times and offer every day a greater number of attractions and activities to visit. The problem is that, when a tourist visits a theme park, he has a short space of time and he wants to maximize the usefulness of the visit, such as enjoying as many attractions as possible. Visitors face a serious selection problem - they must identify the best alternatives so as to optimally utilize their time and visit to the attractions that most interest them, besides keeping a check on the money spent during the visit. It would be very useful if they had a tool to help them take an optimum decision from among the different alternatives, considering their goals, restrictions and preferences. Therefore, we are going to develop a tool that, through a multi-objective model, helps theme park visitors who want to obtain an ideal route, helping them choose among the various alternatives: what activities to pursue, in what order, at what time, etc. The system can be used from home through a web page or application, or when present in the park, which also allows the tourist to incorporate the suggestions that arise in the park on the fly. This tool could improve the satisfaction of tourists visiting the park as it offers the maximum utility with regard to the activities undertaken within the timeframe available to them, thus also rendering added value to the theme park. One of the challenges facing theme parks management is the management of visitor flow, characterized by the dual objective of ensuring the highest quality experience for the tourists and reducing the risks arising from congestion of the different areas and/or most visited attractions, and we consider that this tool can help them to do it.

关键词： Tourist routes multi-objective programming tourist assistance system information and communications technology theme parks decision making

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Portfolio Research Based on Neural Network and multi-objective programming

Portfolio Research Based on Neural Network and Multi-Objecti...

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作者： Rongjie Jian Tingting Ni Xiamen Huaxia University Xiamen Xingcai Vocational&Technical College

In financial investment, risk and benefit coexist. How to balance the benefits and risks and find the optimal investment portfolio is a key issue to be considered by investors. In this research, BP neural network is used to predict the future return on equity(ROE) of asset;a multiobjective programming model of investment portfolio is established on the basis of Markowitz's portfolio investment theory;to select the optimal investment portfolio, a comparison is made on the benefit-risk ratio of the investment portfolio with the smallest risk and at different income levels;in addition, an empirical analysis is made on the basis of the quarterly ROE data of 5 stocks during 2002-2017.

关键词： portfolio BP neural network ROE (return on equity) multi-objective programming benefit–risk ratio

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Investment Decision Model Based on multi-objective programming

Investment Decision Model Based on Multi-objective Programmi...

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作者： Yukun Lu Yuqian Hu Chen Ai College of Mathematics Science Huaqiao University

The design of a portfolio investment strategy for multiple venture capital and a risk-free asset in the market needs to consider two objectives: the overall return is as large as possible and the overall risk is as small as possible. However, the two objectives are not mutually reinforcing. In a certain sense, they are opposite. In this paper, the multi-objective decision-making method is used to establish the model, and the investment benefit is the goal. The optimization model is established for the investment problem. Different investment methods have different risks and benefits. According to the principle of the optimization model, the model proposes two criteria, so that the economic benefits are as large as possible and the risks are as small as possible under certain conditions of investment. At the same time, a linear programming model for portfolio investment scheme design is given. The main idea is to integrate two design goals through linear weighting: assuming that the transaction fee function is approximately linearized on the basis of considerable investment scale, and the risk function is solved by decision variables.

关键词： Portfolio multi-objective programming Linear programming Linear Weighting

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A multi-objective programming Model for Subway Last Train Timetabling 3rd

A Multi-objective Programming Model for Subway Last Train Ti...

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3rd International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT)

作者： Xiang, Wanxiao Wang, Yanhui Beijing Jiaotong Univ Sch Traff & Transportat State Key Lab Rail Traff Control & Safety 3 Shang Yuan Cun Beijing Peoples R China

ISBN: (纸本)9789811079894;9789811079887

Subway last train timetabling focuses more on train coordination to make passengers transfer smoothly. Aiming to find an optimal balanced timetabling, a multi-objectives programming model is proposed with speed profile control for finding the optimal train velocity on sections and train dwell time at stations. Our work makes two contributions. First, this paper analyzes train movements in a line and provides an energy flow transferring method. Second, based on the analysis of train velocity and energy flow, an optimization model, in which passenger satisfaction, train trip time and network energy consumption are model objectives, is brought into the last train timetabling. Finally, to obtain an approximately optimal scheduling strategy, an artificial intelligence algorithm is proposed in particular to effectively solve the proposed model. The results of numerical experiments demonstrate the efficiency and effectiveness of the proposed method.

关键词： Subway Last train timetabling multi-objective programming Train coordination

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Non-smooth multi-objective fractional programming problem involving higher order functions

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INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS 2019年第4期10卷 351-363页

作者： Kharbanda, Pallavi Agarwal, Divya Higher Educ Dept Math Panchkula India Amity Univ Amity Inst Appl Sci Dept Math Noida India

In this paper, a new generalised class of higher order (F, alpha, rho, d)-V-type I function is introduced for a non-smooth multi-objective fractional programming problem involving support functions. The newly defined class extends several known classes in the literature has been justified through a non-trivial example. In the framework of new concept, we determine conditions under which a fractional function becomes higher order (F, alpha, rho, d)-V-type I function and do some computational work to substantiate the analysis. Further, we establish Karush-Kuhn-Tucker type sufficient optimality conditions and derive various duality results for higher order Mond-Weir type and Schaible type dual programs.

关键词： multi-objective programming (F, alpha, rho, d)-V-type I function fractional programming nonlinear programming efficient solution

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An inexact multi-objective programming model for an economy-energy-environment system under uncertainty: A case study of Urumqi, China

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ENERGY 2017年 126卷 165-178页

作者： Fu, Z. H. Xie, Y. L. Li, W. Lu, W. T. Guo, H. C. Peking Univ Coll Environm Sci & Engn Beijing 100871 Peoples R China Univ Sci & Technol Beijing Beijing 100871 Peoples R China North China Elect Power Univ China Canada Energy & Environm Res Ctr Beijing 102206 Peoples R China

Economic restructuring, energy planning and environmental protection are subject to inherent uncertainties in a compound system with competing decision objectives. Therefore, an inexact multi objective programming model for regional economy-energy-environment system management has been developed to obtain absolutely "optimal" solutions. Under two comparative scenarios, three subsystems, six industries, four types of energy, and three kinds of air pollution were considered in an optimization model, and a net system benefit and trade-off analysis between subsystems was conducted. The methods of interval-parameter programming and multi-objective programming were incorporated into the model to tackle the uncertainties and complexities reflected in the case study. The model results indicated that the developed model could provide effective linkages among the economy-energy environment systems and offer decision makers great insight into the reliability tradeoffs for the adjustment of the existing management policy. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： multi-objective programming Economy-energy-environment system Regional development plan Uncertainty

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