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Some new generalized aggregation operators for triangular intuitionistic fuzzy numbers and application to multi-attribute group decision making

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COMPUTERS & INDUSTRIAL ENGINEERING 2016年 93卷 286-301页

作者： Wan, Shu-Ping Wang, Feng Lin, Li-Lian Dong, Jiu-Ying Jiangxi Univ Finance & Econ Coll Informat Technol 168 Shuang Gang East Rd Nanchang 330013 Peoples R China Jiangxi Univ Finance & Econ Sch Stat Nanchang 330013 Peoples R China Jiangxi Univ Finance & Econ Res Ctr Appl Stat Nanchang 330013 Peoples R China

The aim of this paper is to develop some new generalized aggregation operators for triangular intuitionistic fuzzy numbers (TIFNs) and apply to multi-attribute group decision making (MAGDM) problems. First, the weighted possibility attitudinal expected values of TIFNs are defined and a new method is presented to rank TIFNs considering risk attitude of decision maker (DM). The sensitivity analyses on attitudinal character parameter are given. Then, the triangular intuitionistic fuzzy weighted averaging (TIFWA) operator, ordered weighted averaging (TIFOWA) operator, ordered weighted geometric (TIFOWG) operator and hybrid weighted averaging (TIFHWA) operator are defined. We further develop some new generalized aggregation operators for TIFNs, involving the triangular intuitionistic fuzzy generalized ordered weighted averaging (TIFGOWA) operator and generalized hybrid weighted averaging (TIFGHWA) operator. Some desirable properties for these operators are discussed in detail. Utilizing the TIFGHWA and TIFWA operators, we propose a new method for MAGDM with TIFNs and incomplete weight information. In this method, DMs' weights are determined by Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the weights of attributes are objectively derived through constructing a multi-objective programming model which is transformed into a linear goal program to solve. Finally, the example analysis of an investment selection example verifies the effectiveness and practicability of the proposed method in this paper. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： multi-attribute group decision making Triangular intuitionistic fuzzy number Generalized ordered weighted averaging Generalized hybrid weighted averaging multi-objective programming

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multi-objective probabilistically constrained programs with variable risk: Models for multi-portfolio financial optimization

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2016年第2期252卷 522-539页

作者： Lejeune, Miguel A. Shen, Siqian George Washington Univ Washington DC USA Univ Michigan Ann Arbor MI 48109 USA

We consider a class of multi-objective probabilistically constrained programs (MOPCP) with a joint probabilistic constraint and a variable risk level. We consider two cases with only a random right-hand side vector or a multi-row random technology matrix, and propose a Boolean modeling framework to derive new mixed-integer linear programs (MILP) that are either equivalent reformulations or inner approximations of MOPCP, respectively. Via testing randomly generated MOPCP instances, we demonstrate modeling insights pertaining to the most suitable MILP, to the trade-offs between conflicting objectives of cost/revenue and reliability, and to the parameter scalarization determining relative importance of each objective. We then focus on several MOPCP variants of a multi-portfolio financial optimization problem to implement a downside risk measure, which can be used in a centralized or decentralized investment context. We study the impact of modeling parameters on the portfolios, show, via a cross-validation study, robustness of MOPCP, and perform a comparative analysis of the optimal investment decisions. (C) 2016 Elsevier B.V. All rights reserved.

关键词： multi-portfolio optimization Probabilistic constraint Variable reliability multi-objective programming Boolean programming

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Minimum Weighted Minkowski Distance Power Models for Intuitionistic Fuzzy Madm with Incomplete Weight Information

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INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 2017年第5期16卷 1387-1408页

作者： Li, Deng-Feng Wan, Shu-Ping Fuzhou Univ Sch Management 2 Xueyuan Rd Fuzhou 350108 Fujian Peoples R China Jiangxi Univ Finance & Econ Coll Informat Technol Nanchang 330013 Jiangxi Peoples R China

Owing to more vague concepts frequently represented in decision data, intuitionistic fuzzy sets (IFSs) are more fliexibly used to model real-life decision situations. At the same time, with ever increasing complexity in many decision situations in reality, there are often some challenges for a decision maker to provide complete attribute preference information, i.e., the weights may be completely unknown or partially known. The aim of this paper is to develop an effiective method for solving intuitionistic fuzzy multi-attribute decision making (MADM) problems with incomplete weight information. In this method, ratings of alternatives on attributes are expressed with IFSs. The multi-objective programming models are established to calculate unknown weights by using weight information partially known a priori. The derived minimum weighted Minkowski distance power models are used to determine the unknown weights and to generate the ranking order of the alternatives simultaneously. The proposed models are easily extended to intuitionistic fuzzy MADM problems with different weight information structures. An example of the supplier selection problem is examined to demonstrate applicability and flexibility of the proposed models and method.

关键词： Intuitionistic fuzzy set multi-attribute decision making uncertainty modeling multi-objective programming distance measure

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A Decision Support Methodology for Locating Bank Branches: A Case Study in Turkey

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INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 2017年第1期16卷 59-86页

作者： Basar, Ayfer Kabak, Ozgur Topcu, Y. Ilker Istanbul Tech Univ Dept Ind Engn Macka Campus TR-34357 Istanbul Turkey

This paper presents an integrated decision support methodology for locating bank branches. The methodology is composed of two stages: problem structuring, and modeling. In the first stage, initially, a number of criteria are selected with the help of a detailed literature review and expert opinions. Subsequently, importance weights of these criteria for different types of bank branches are identified based on judgments of experts for pairwise comparison questions. At the modeling stage, considering the characteristics and importance of the criteria, a novel multiobjective mathematical programming model is proposed to find specific locations of bank branches. The proposed methodology is applied in locating branches of a Turkish bank. In order to test the validity of the results and robustness, a sensitivity analysis is conducted and the solutions are found to be robust.

关键词： Decision-making problem structuring bank branches location multi-objective programming real life application

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Fuzzy Stochastic Genetic Algorithm for Obtaining Optimum Crops Pattern and Water Balance in a Farm

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WATER RESOURCES MANAGEMENT 2016年第12期30卷 4097-4123页

作者： Dutta, S. Sahoo, B. C. Mishra, Rajashree Acharya, S. KIIT Univ Sch Appl Sci Dept Math Bhubaneswar Orissa India Orissa Univ Agr & Technol Coll Agr Engn & Technol Dept Soil & Water Conservat Engn Bhubaneswar Orissa India

This paper is concerned with multi-objective fuzzy stochastic model for determination of optimum cropping patterns with water balance for the next crop season. The objective functions of the model is to study the effect of various cropping patterns on crop production subject to total water supply in a small farm. The decision variables are the cultivated area of different crops at the farm. The water requirement of the crops follows fuzzy uniform distribution and yields in the objective functions are taken as a fuzzy numbers. The model is solved by using fuzzy stochastic simulation based genetic algorithm without deriving the deterministic equivalents.

关键词： Cropping pattern Water balance Genetic algorithm Fuzzy stochastic programming multi-objective programming

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Water quality management in a wetland system using an inexact left-hand-side chance-constrained fuzzy multi-objective approach

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STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2016年第2期30卷 621-633页

作者： Ji, Yao Huang, Guohe Sun, Wei Li, Yanfeng North China Elect Power Univ SC Resources & Environm Res Acad MOE Key Lab Reg Energy & Environm Syst Optimizat Beijing 102206 Peoples R China Univ Regina Inst Energy Environm & Sustainable Commun Regina SK S4S 0A2 Canada

Water quality management is a significant item in the sustainable development of wetland system, since the environmental influences from the economic development are becoming more and more obvious. In this study, an inexact left-hand-side chance-constrained fuzzy multi-objective programming (ILCFMOP) approach was proposed and applied to water quality management in a wetland system to analyze the tradeoffs among multiple objectives of total net benefit, water quality, water resource utilization and water treatment cost. The ILCFMOP integrates interval programming, left-hand-side chance-constrained programming, and fuzzy multi-objective programming within an optimization framework. It can both handle multiple objectives and quantify multiple uncertainties, including fuzziness (aspiration level of objectives), randomness (pollutant release limitation), and interval parameters (e. g. water resources, and wastewater treatment costs). A representative water pollution control case study in a wetland system is employed for demonstration. The optimal schemes were analyzed under scenarios at different probabilities (pi, denotes the admissible probability of violating the constraint i). The optimal solutions indicated that, most of the objectives would decrease with increasing probability levels from scenarios 1 to 3, since a higher constraint satisfaction probability would lead to stricter decision scopes. This study is the first application of the ILCFMOP model to water quality management in a wetland system, which indicates that it is applicable to other environmental problems under uncertainties.

关键词： Inexact chance-constrained programming multi-objective programming Water quality Wetland Uncertainty

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The "weak-link" approach to network DEA for two-stage processes

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2016年第2期254卷 481-492页

作者： Despotis, Dimitris K. Koronakos, Gregory Sotiros, Dimitris Univ Piraeus Dept Informat 80 Karaoli & Dimitriou Piraeus 18534 Greece

We introduce in this paper a new definition for the overall system efficiency in network DEA, which is inspired by the "weak link" notion in supply chains and the maximum-flow/minimum- cut problem in networks. We use a two-phase max-min optimization technique in a multi-objective programming framework to estimate the individual stage efficiencies and the overall system efficiency in two-stage processes of varying complexity. This enables us to estimate unique and unbiased efficiency scores and, if required, to drive the efficiency assessments effectively in line with specific priorities given to the stages. A comparison with the multiplicative decomposition approach on data drawn from the literature brings into light the advantages of our method. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Network DEA Two-stage processes Weak link multi-objective programming

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Optimization and Evaluation of Environmental Operations for Three Gorges Reservoir

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WATER RESOURCES MANAGEMENT 2016年第10期30卷 3553-3576页

作者： Hu, Ming Huang, Guo H. Sun, Wei Ding, Xiaowen Li, Yongping Fan, Bin Chinese Acad Sci Res Ctr Ecoenvironm Sci State Key Lab Environm Aquat Chem Beijing 100085 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China North China Elect Power Univ SC Resources & Environm Res Acad MOE Key Lab Reg Energy & Environm Syst Optimizat Beijing 102206 Peoples R China Univ Regina Fac Engn & Appl Sci Environm Syst Engn Program Regina SK S4S 0A2 Canada Univ Regina Inst Energy Environm & Sustainable Commun Regina SK S4S 7H9 Canada

This study proposed a multi-objective environmental reservoir operation methodology (MOEROM) and applied the new methodology to the Three Gorges Reservoir (TGR) in China. The MOEROM directly incorporated the statistical water quality models in the objective functions to reflect the response relationships between reservoir operations and water quality in three tributaries (the Xiangxi River, the Daning River and the Xiaojing River). A real-coded genetic algorithm with self-adaptive crossover operators was employed to solve the environmental reservoir operation model. And four different MCDA approaches (AHP, TOPSIS, Fuzzy AHP, and Fuzzy TOPSIS) were proposed to evaluate the optimal operational schemes. The results showed that TOPSIS and AHP were more suitable for selecting the schemes than the others because of the larger fluctuations. To demonstrate the advantage of MOEROM, the environmental operation schemes were compared with traditional and practical operation schemes in 2013. The advantages of the environmental operation scheme over the others were that it would help reach a compromise between economic benefit, flood control and water quality improvement. In the future, more water quality indices, uncertainties in water environmental information, and more efficient algorithms would be further considered and researched.

关键词： multi-objective programming Environmental operation Genetic algorithm MCDA Three Gorges Reservoir

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Optimization of industry structure based on water environmental carrying capacity under uncertainty of the Huai River Basin within Shandong Province, China

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JOURNAL OF CLEANER PRODUCTION 2016年第Part5期112卷 4594-4604页

作者： Li, Na Yang, Hong Wang, Lachun Huang, Xianjin Zeng, Chunfen Wu, Hao Ma, Xiaoxue Song, Xuetao Wei, Yanan Nanjing Univ Sch Geog & Oceanog Sci Nanjing 210046 Jiangsu Peoples R China Univ Oslo CEES Dept Biosci N-0316 Oslo Norway Shandong Acad Environm Sci Jinan 250013 Peoples R China

Optimization of the industry structure is important for the sustainable development for developing countries, e.g. China. The inexact stochastic multiple objective programming (ISMOP) which integrates stochastic programming, interval linear programming, and multiple objective programming was applied to analyze the optimization of industrial structure based on water environmental carrying capacity in Huai River Basin within Shandong Province (HRBSP). ISMOP can effectively solve the uncertainty existing in the multiple-objective optimization model and provide the information of development patterns of different industrial sectors. Results showed that the growth rates of output values from secondary industries under different q(i) values in the planning stage (2010-2020) will be almost 8%, and the total amounts of COD and NH3-N discharge will reduce by at least 65% from 2010 to 2020 in HRBSP. In term of the secondary industrial structure, the coal, paper-making and food processing industries, as the traditional backbone industries but with high risk of water pollution, should be reduced gradually;the beverage and textile industries should be strictly limited;and conversely, the new industries, such as metallurgy and construction material industries, should be allowed to maintain the rapid development. In the context of the aquatic environment protection in the basin level, the results based on ISMOP are useful for making policies to balance the economic development and water pollutant prevention within the Huai River Basin and other river basins. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Inexact stochastic programming multi-objective programming Industry structure Water resources carrying capacity Sustainable development Huai River Basin

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An integrated model for green partner selection and supply chain construction

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JOURNAL OF CLEANER PRODUCTION 2016年第Part3期112卷 2114-2132页

作者： Wu, Chong Barnes, David Xiamen Univ Sch Management Xiamen 361005 Peoples R China Univ Westminster Westminster Business Sch London NW1 5LS England

Stricter governmental regulations and rising public awareness of environmental issues are pressurising firms to make their supply chains greener. Partner selection is a critical activity in constructing a green supply chain because the environmental performance of the whole supply chain is significantly affected by all its constituents. The paper presents a model for green partner selection and supply chain construction by combining analytic network process (ANP) and multi-objective programming (MOP) methodologies. The model offers a new way of solving the green partner selection and supply chain construction problem both effectively and efficiently as it enables decision-makers to simultaneously minimize the negative environmental impact of the supply chain whilst maximizing its business performance. The paper also develops an additional decision-making tool in the form of the environmental difference, the business difference and the eco-efficiency ratio which quantify the trade-offs between environmental and business performance. The applicability and practicability of the model is demonstrated in an illustration of its use in the Chinese electrical appliance and equipment manufacturing industry. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Partner selection Green supply chain ANP multi-objective programming

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