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Modified two-phase fuzzy goal programming integrated with IF-TOPSIS for green supplier selection

APPLIED SOFT COMPUTING 2020年 93卷 106371-106371页

作者： Kilic, Huseyin Selcuk Yalcin, Ahmet Selcuk Marmara Univ Dept Ind Engn TR-34722 Istanbul Turkey Okan Univ Dept Ind Engn TR-34959 Istanbul Turkey

The environmental consciousness of society and globally competitive market have considerably increased thanks to the scientific studies, media, governmental and non-governmental organizations. In this regard, environmental factors have been considered within the supplier selection process which is a major decision point in supply chains. Hence, in addition to the optimization of the traditional criteria, green criteria have also started to take its place in the supplier selection problem. In this study, an integrated methodology including the Intuitionistic Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) and a modified two-phase fuzzy goal programming model are proposed to better address this selection problem in a multi-item/multi-supplier/multi-period environment. The detailed steps are explicitly provided within the proposed methodology. In this respect, the criteria importance weights are determined via IF-TOPSIS which enables the opportunity to handle the vagueness within the evaluation process of decision-makers. Afterward, the obtained importance weights are used in the modified two-phase fuzzy goal programming model for selecting the best suppliers. An application in the air filter industry is performed to demonstrate the validation of the proposed methodology. Consequently, the proposed methodology successfully provides the best selection of suppliers by satisfying both classic and green criteria. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Green supplier selection Intuitionistic fuzzy TOPSIS Two-phase fuzzy goal programming multi-objective programming

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A Linear programming Priority Method for a Fuzzy Transportation Problem with Non-linear Constraints - The Case of a General Contractor Company

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FUZZY INFORMATION AND ENGINEERING 2011年第2期3卷 193-208页

作者： Barough, Hossein Abdollahnejad Payame Noor Univ Dept Ind Engn Tehran Iran

Demand and supply pattern for most products varies during their life cycle in the markets. In this paper, the author presents a transportation problem with non-linear constraints in which supply and demand are symmetric trapezoidal fuzzy value. In order to reflect a more realistic pattern, the unit of transportation cost is assumed to be stochastic. Then, the non-linear constraints are linearized by adding auxiliary constraints. Finally, the optimal solution of the problem is found by solving the linear programming problem with fuzzy and crisp constraints and by applying fuzzy programming technique. A new method proposed to solve this problem, and is illustrated through numerical examples. multi-objective goal programming methodology is applied to solve this problem. The results of this research were developed and used as one of the Decision Support System models in the Logistics Department of Kayson Co.

关键词： Fuzzy transportation Non-linear programming multi-objective programming Fuzzy linear programming Stochastic programming

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Smart Optimization Design of Urban Group Chain Travel Routes 20

Smart Optimization Design of Urban Group Chain Travel Routes

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20th COTA International Conference of Transportation Professionals (CICTP) - Advanced Transportation, Enhanced Connection

作者： Zhang, Wen Hu, Xiaowei Zeng, Yongquan Harbin Inst Technol Sch Transportat Sci & Engn Huanghe Rd Harbin Heilongjiang Peoples R China

ISBN: (数字)9780784482933

ISBN: (纸本)9780784482933

With the improvement of people's living standards and the desire to pursue quality of travel, the number of people who choose self-guided itineraries is increasing sharply. However, the problem is that planning routes during the trip are exhausting, and the efficiency of transportation. In response to this and considering the psychology of people making the most of their holidays along with current boom in chain travel, the paper proposes a frame and an algorithm that aims to optimize the travel route. This paper studies route planning for chain travel of city groups within a specific range based on cluster analysis. The algorithm refers to the solution of TSP, knowledge in Graph Theory, and is suitable for optimizing travel itineraries for multiple cities for several days, characterized by providing users with time and money-saving options. It reduces waste on the road, waiting times for travelers, and provides convenience for self-guided itineraries.

关键词： City groups Chain travel Transportation big data multi-objective programming TSP

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multi-objective Production Planning Considering Partner Selection for Networked Manufacturing

Multi-Objective Production Planning Considering Partner Sele...

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19th International Conference on Industrial Engineering and Engineering Management

作者： Chen, Zhi-xiang Li, Li Sun Yat Sen Univ Dept Management Sci Guangzhou Guangdong Peoples R China Sun Yat Sen Univ Int Business Zhuhai Peoples R China

ISBN: (纸本)9783642384271;9783642384264

This paper studies an integrated optimization model of production planning with partner selection in a networked manufacturing system. An integrated multi-objective programming model is proposed and a numerical example is illustrated. The result shows the effectiveness and feasibility of the model. The model is suitable for the decision of production planning in networked manufacturing environment.

关键词： Production planning Partner selection multi-objective programming Networked manufacturing

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Application of multi-Choice Fuzzy Linear programming Problem to a Garment Manufacture Company

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JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES 2015年第6期36卷 569-593页

作者： Acharya, Srikumar Biswal, M. P. KIIT Univ Sch Appl Sci Dept Math Bhubaneswar Orissa India Indian Inst Technol Dept Math Kharagpur 721302 W Bengal India

In this paper, we consider a fuzzy multi-choice linear programming problem where some of the parameters and decision variables are trapezoidal type fuzzy numbers. In order to defuzzify a general fuzzy quantity the concept of nearest trapezoidal fuzzy number is introduced. By assuming all the decision variables as trapezoidal fuzzy number, the objective function and the left hand side of constraints are approximated to their nearest trapezoidal fuzzy number. Interpolating polynomials are formulated for all multi-choice type parameters. multi-choice type parameters are replaced by polynomials with integer variables. Then an equivalent multi-objective non linear programming problem is established. First and second objective functions represent left and right modal values of the trapezoidal type fuzzy number, where as the third and fourth objective functions represent the left and right spreads of the trapezoidal type fuzzy number. By applying lexicographic method optimal solution is obtained. In addition, a case study on a garment manufacture company is presented to demonstrate the solution procedure.

关键词： Fuzzy programming Problem multi-Choice programming multi-objective programming Mixed Integer programming

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Study on A Dynamic Traffic Route Choice Model with Travel Time Reliability Constrains of Intelligent Transportation Systems 5

Study on A Dynamic Traffic Route Choice Model with Travel Ti...

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5th IEEE International Conference on Software Engineering and Service Science (ICSESS)

作者： Sun, Xiaomei Changchun Vocat Inst Technol Sch Engn Technol Changchun Jilin Province Peoples R China

ISBN: (纸本)9781479932795

For Intelligent Transportation Systems(ITS), dynamic traffic route choice is one of the most important technologies. Practical applications have shown that static route choice models can not meet passengers' travel demands, because route choice is a typical multi-objective programming problem affected by many dynamic factors, such as real-time traffic state, link travel time, traffic incident, intersection delay and so on. In this paper, I proposed a multi-objective dynamic route choice function with the minimum of link travel time and distance as the target, which travelers paid most attention to when they chose the route. Also I got travel time reliability as the model constraint to against the complexity and indetermination of traffic flow. And I obtained the link travel time by short-term forecasting based on measured traffic data of the network. Finally, in order to test its reliability, I established a simulation road network for real-time traffic data, and solved the model I put forward by improved genetic algorithm. Fortunately, I obtained an exciting result.

关键词： Route choice model travel time reliability improved genetic algorithm multi-objective programming

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Decision Support System and multi-Criteria Decision Aid: A State of the Art and Perspectives

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JOURNAL OF multi-CRITERIA DECISION ANALYSIS 2015年第1-2期22卷 101-117页

作者： Razmak, Jamil Aouni, Belaid Laurentian Univ Sudbury ON P3E 2C6 Canada Qatar Univ Coll Business & Econ Dept Management & Mkt POB 2713 Doha Qatar

The aim of this paper is to highlight the role of the Decision Support System within the field of multi-criteria decision aid (MCDA). The MCDA tools have been incorporated into systems to create multi-Criteria Decision Support Systems (MCDSSs). In our literature review, we noticed that more than 100 papers have been written over a 20-year period in which MCDSS was used as a decision-making tool. The present paper describes some real applications of MCDSS in different fields, harmoniously combined with decision-making methods such as analytic hierarchy process, Utility Additive, and Goal programming. The present study proposes an integrative MCDSS evaluation through guidance on the tools most useful for a specific user with a particular decision problem. Copyright (C) 2014 John Wiley & Sons, Ltd.

关键词： Decision Support System multi-Criteria Decision Aid multi-objective programming Typology

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A robust optimization model for multi-objective operation of supply chain under uncertain market

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26th Chinese Control Conference

作者： Xu Jiawang Huang Xiaoyuan Shenyang Inst Aeronaut Engn Dept Management Shenyang 110136 Liaoning Peoples R China Northeastern Univ Sch Business Adm Shenyang 110004 Peoples R China

ISBN: (纸本)9787811240559

A multi-objective operation model is proposed in this paper to deal with a multi-product, multi-period supply chain consisting of a supplier and a producer. In this supply chain, the amount of raw materials supply and their prices, ultimate products demand and their prices are uncertain. The uncertainties of prices are described by the uncertain intervals;the supplies and demands are described as a scenario set with certain probability. The model is constructed as a multi-objective programming problem to satisfy several conflict objectives, such as the operating coordination of supply chain, making the maximum profit of all participants as much as possible, and robustness of decision to uncertain markets. The result of a numerical example shows that the model we proposed is robust.

关键词： supply chain operation management robust optimization uncertainty multi-objective programming

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Game theory versus multi-objective model for evaluating multi-level structure by using data envelopment analysis

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INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT 2017年第4期12卷 245-255页

作者： Rezaee, Mustafa Jahangoshai Shokry, Mahnush Urmia Univ Technol Fac Ind Engn Orumiyeh Iran

Data envelopment analysis (DEA) is a well-known approach to measuring operations performance of decision-making units (DMUs). Moreover, the balanced scorecard (BSC) is a methodology for strategic planning of organizations and measuring their internal performance. DEA generally uses quantity measures, whereas BSC applies quality measures. In the real world, DMUs usually have complex structures such as multi-level or hierarchical structures. In these structures, there are multiple levels and each level utilizes inputs to produce outputs separately, where the outputs of the previous level are the inputs to the next level. In the present paper, we apply BSC to the design of a multi-level structure. BSC encompasses the four perspectives of finance, customers, internal processes, and learning & growth. Furthermore, we apply DEA to multi-stage or hierarchical structures based on BSC. For this purpose, two different approaches, the cooperative model versus the multi-objective model, are proposed. Cooperative models such as bargaining games are game theoretic approaches to evaluate DMUs. In this paper, the DEA-game model uses the bargaining concept to link perspectives in BSC, while each perspective is considered separately as an objective in the multi-objective DEA model. In addition, two approaches are compared based on the related results. We also employ data on Iranian cement companies to show the different capabilities of each approach. Our findings demonstrate that the DEA-game model is capable of differentiating the cement companies from each other more effectively.

关键词： Data envelopment analysis bargaining game multi-level structures multi-objective programming balanced scorecard operations performance

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A modified TOPSIS approach for solving stochastic fuzzy multi-level multi-objective fractional decision making problem

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OPSEARCH 2020年第4期57卷 1374-1403页

作者： El Sayed, M. A. Baky, Ibrahim A. Singh, Pitam Benha Univ Dept Basic Engn Sci Fac Engn Elqalyoubia Egypt Tabuk Univ Fac Sci Dept Math Tabuk Saudi Arabia Motilal Nehru Natl Inst Technol Dept Math Allahabad Prayagraj 211004 India

This paper presents a new modified technique for order preference by similarity to ideal solution (M-TOPSIS) approach for unraveling stochastic fuzzy multi-level multi-objective fractional decision making problem (ML-MOFDM) problem. In the proposed model the coefficients and the scalars of the fractional objectives have a fuzzy nature. The right-hand sides are stochastic parameters also, both of the left-hand side coefficients and the tolerance measures are fuzzy kind. In this manner, the deterministic-crisp ML-MOFDM model of stochastic fuzzy ML-MOFDM can be gotten utilizing chance constrained strategy with predominance plausibility criteria and the alpha-cut methodology. In literature, almost all works on multi-level fractional programming are the crisp version, in which they convert the fractional functions into a linear one using a first order Taylor series which causes rounding off error. The proposed M-TOPSIS approach presents a new method for solving such problem without approximating or changing the nature of the problem. An algorithm to clear up the M-TOPSIS approach, just as illustrative numerical model is displayed.

关键词： multi-level optimization multi-objective programming TOPSIS Fractional programming Chance constrained programming Fuzzy sets

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