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A new intelligent algorithm for dynamic facility layout problem in state of fuzzy constraints

NEURAL COMPUTING & APPLICATIONS 2014年第5期24卷 1179-1190页

作者： Kaveh, Mojtaba Dalfard, Vahid Majazi Amiri, Sajjad Islamic Azad Univ Firoozabad Branch Dept Business Adm Firoozabad Iran Islamic Azad Univ Kerman Branch Young Res & Elites Club Kerman Iran Sirjan Technol Univ Dept Math & Comp Sci Sirjan Iran

In the present paper, the dynamic facilities layout problem is studied in presence of ambiguity of information flow. Product demand (and consequently material flow) is defined as fuzzy numbers with different membership functions. The problem is modeled in fuzzy programming. Three models of expected value, chance-constrained programming and dependent-chance programming and two hybrid intelligent algorithms are then presented. At the end, efficiency of algorithms for solving fuzzy models of dynamic facilities layout is shown through some numerical examples.

关键词： Dynamic facilities layout problem fuzzy programming Hybrid intelligent algorithm Genetic algorithm Simulated annealing algorithm

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Integrated modeling approach for sustainable municipal energy system planning and management - A case study of Shenzhen, China

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JOURNAL OF CLEANER PRODUCTION 2014年 75卷 143-156页

作者： Zhou, Y. Li, Y. P. Huang, G. H. North China Elect Power Univ Sino Canada Resources & Environm Res Acad MOE Key Lab Reg Energy Syst Optimizat Beijing 102206 Peoples R China

In this study, a fractile-based interval mixed-integer programming (FIMP) method is advanced for sustainable municipal-scale energy system planning and management. FIMP can handle uncertainties presented in terms of fuzzy boundary intervals that represent interval coefficients with independently fuzzy lower and upper bounds with possibility distributions. A FIMP-based municipal energy model (FIMP-MEM) is then formulated for managing various energy activities in the City of Shenzhen, China. Solutions for energy supply, electricity generation, oil-product production, air-pollutant mitigation, carbon dioxide control, capacity expansion, and electricity import/export are obtained. Results can be used to help the city's managers to identify desired system designs and to determine which of these designs can most efficiently accomplish optimizing the system objective under diverse p-necessity fractiles. The generated decision alternatives are beneficial for the city's energy system planning and management through (a) generating desired energy resources allocation, (b) identifying electricity generation and capacity-expansion scheme, (c) providing air pollution control plan, (d) analyzing the tradeoff among system cost, environmental impact, and system-failure risk. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Air pollution control fuzzy programming Management Municipal energy system Policy analysis Uncertainty

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Multiobjective optimal control of the linear wave equation

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AIN SHAMS ENGINEERING JOURNAL 2014年第4期5卷 1299-1305页

作者： Zarei, Hassan Bahrmand, Mehdi Rezai Payame Noor Univ Dept Math Tehran Iran

In this paper, we propose a method for the solution of a multiobjective optimal control problem (MOOCP) in a linear distributed-parameter system governed by a wave equation. An explicit solution for the wave equation is derived and the control problem of this distributedparameter system is reduced to an approximate multiobjective programming problem. The fuzzy goals are incorporated for objectives and the equilibrium problem in terms of maximization of the degree of attainment for the aggregated fuzzy goals is considered. The solution of the equilibrium optimization problem is a Pareto optimal solution with the best satisfaction performance which is achieved by using a metaheuristic algorithm such as the simulated annealing (SA) together with the simplex method of linear programming (LP) problems. An illustrative numerical example is presented to indicate the efficiency of the proposed method and the capability of the SA in finding optimal solution compared with two popular metaheurestics. (C) 2014 Production and hosting by Elsevier B. V. on behalf of Ain Shams University.

关键词： Linear distributed-parameter systems Multiobjective optimal control Multiobjective programming fuzzy programming fuzzy goals Metaheuristic algorithms

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A Group Method of Symmetric Triangular fuzzy Numbers Handling and Its Application to Analyze Monitoring Data of Small and Micro Enterprises in Sichuan Province 21

A Group Method of Symmetric Triangular Fuzzy Numbers Handlin...

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21st International Conference on Management Science & Engineering (ICMSE)

作者： Wang Rui Peng Ting Li Xi-feng Sichuan Univ Sch Business Chengdu 610064 Peoples R China

ISBN: (纸本)9781479953769

Group method of data handling has been proven an effective knowledge mining tool to emerge the influencing factors of enterprises growth in the past researches, but when employed to analyze the small and micro enterprises in Sichuan Province, its effectiveness is reduced by the noise in the data obtained from the enterprises' produce and business operations monitor platform website. In order to increase the noise immunity of the method, the monitoring data is firstly processed as some symmetric triangular fuzzy numbers in this paper, and the parameter estimation technique for all self-organized models named partial functions in the method is changed from the former regression analysis with determined training data set to the fuzzy programming with fuzzy set. Basing on this transform, a group method of the symmetric triangular fuzzy numbers handling is presented and the result of its empirical study in Sichuan Province proves the method is able to disclose some key influencing factors of the small and micro enterprises' growth with unstable and noisy monitoring data.

关键词： group method of data handling symmetric triangular fuzzy number fuzzy programming multi-layer algorithm small and micro enterprises

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A fuzzy Two-stage Project Portfolio Selection Model Addressing Financial and Non-financial Factors

A Fuzzy Two-stage Project Portfolio Selection Model Addressi...

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26th Chinese Control and Decision Conference (CCDC)

作者： Qin, Quande Li, Jinpeng Li, Li Shenzhen Univ Sch Management Shenzhen 5180060 Peoples R China

ISBN: (纸本)9781479937066

Trade-off between financial and non-financial factors is crucial for project portfolio selection. In this paper, a two-stage project portfolio selection model, which addresses these two factors, is proposed. In the proposed two-stage model, the return and cost of projects are characterized by triangular fuzzy number. In the first stage, a score model, focusing on the non-financial aspects, uses the Go-Kill threshold value to determine whether a project can be further appraised in the next stage. In the second stage, a fuzzy programming model, addressing the financial aspects, is used to select the optimal combinations from the go-projects of the first stage. Finally, a numerical example is given to demonstrate the effectiveness and applicability of the proposed model.

关键词： Project portfolio selection non-financial factors fuzzy programming

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A multi-objectivities fuzzy programming model in expressway planning

A multi-objectivities fuzzy programming model in expressway ...

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2nd International Conference on Intelligent Computation Technology and Automation

作者： Lu Huapu Yu Xinxin Li Yue Zhao Xiaoqiang Shi Ye Tsinghua Univ Inst Transportat Engn Beijing 100084 Peoples R China

ISBN: (纸本)9780769538044

This paper develops a fuzzy multi-objective programming model for solving the fuzzy multi-objective expressway planning problems. The proposed model aims to minimize the total system costs and the total construction cost with reference to fuzzy available OD. Then the goal programming was proposed. Finally, a numerical example is given to illustrate the ability of the proposed model to expressway system planning.

关键词： fuzzy programming membership function traffic assignment goal programming

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The Expected Value of Imperfect Information to fuzzy programming

The Expected Value of Imperfect Information to Fuzzy Program...

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6th International Symposium on Neural Networks

作者： Zheng, Mingfa Wang, Guoli Kou, Guangxing Liu, Jia AF Engn Univ Dept Appl Math & Phys Xian 710051 Peoples R China Hebei Univ Coll Math & Comp Sci Baoding 071002 Peoples R China

ISBN: (纸本)9783642015090

The paper is concerned with Finding the expected value of imperfect information to two-stage fuzzy programming. In this paper we firstly present the definition which is the sum of pairs expected value, then obtain the definition of expected value of imperfect information based on the concept, and discuss its rationality. In addition, several numerical examples are also given to explain the definitions. The results obtained in this paper can be used to fuzzy optimization as we design algorithm to estimate the value of imperfect information.

关键词： fuzzy programming Expected value of perfect information Expected value of imperfect information

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Model Design for Transmission Congestion Management Based on fuzzy programming

Model Design for Transmission Congestion Management Based on...

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2nd International Workshop on Knowledge Discovery Data Mining

作者： Zhao, Yu Zhao, Bo Qi, Chunjie Huazhong Agr Univ Coll Econ & Management Wuhan Hubei Peoples R China Cent South Univ CSU Sch Mat Sci & Comp Changsha Peoples R China

ISBN: (纸本)9780769535432

Based on data collected previously on the electricity market of the East China, we use stepwise regression method to find the approximate expression of the active power flow of each power sets on East China's certain electrical network. Then classified discussion is carried out according to the difference of the capacity in and out of merit in order to obtain a simple and reasonable rule for calculating the block cost. Based on this, the objective programming model for output distribution of each unit is achieved. Exclude conditions step by step, and adjust the output allocation plan. Introduce flexible factors defining membership function to change fuzzy programming into non-fuzzy programming, and use genetic algorithm to get solution. The model considers both safety and cost so that different network operators can get their preferred allocation plan.

关键词： electrical network transmission congestion management fuzzy programming multiobjective optimization model design

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A new robust fuzzy approach for aggregate production planning

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SCIENTIA IRANICA 2014年第6期21卷 2307-2314页

作者： Rahmani, D. Yousefli, A. Ramezanian, R. KN Toosi Univ Technol Dept Ind Engn Tehran Iran Imam Khomeini Int Univ Dept Ind Management Qazvin Iran

Aggregate production planning is a medium-term production plan that determines the production plan for satisfying fluctuating demand. In this paper, a robust approach is used to formulate aggregate production planning, in which some parameters, such as production cost and customer demand, are fuzzy variables. The concept of entropy is used to reduce the sensitivity of noisy data and to obtain a more robust aggregate production plan, based on the proposed model. Finally, a numerical example is presented to explain the model solution. In addition, the robustness of the proposed model solution is compared with other classical fuzzy programming approaches. (C) 2014 Sharif University of Technology. All rights reserved.

关键词： Aggregate production planning Robust optimization fuzzy programming fuzzy entropy

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A credibility-based fuzzy programming model for APP problem

A credibility-based fuzzy programming model for APP problem

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International Conference on Artificial Intelligence and Computational Intelligence

作者： Zhu, Haiping Zhang, Jian Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Mech Sci & Technol Wuhan 430074 Peoples R China

ISBN: (纸本)9780769538167

We analyze the importance of practical aggregate production planning (APP) under uncertain environment and present a novel fuzzy programming resolution model based on the credibility measure of fuzzy event. The customers' demands, the unit profits and the available manufacturing capacities are all regarded as fuzzy variables;three types of common constraints are re-formulated as fuzzy chance constraints. Considering that the generalized fuzzy optimizing model is difficult to solve, we deduce an equivalent transformation technique on the assumption that the fuzzy variables obey trapezoidal distributions. In this way we convert these models into a equivalent crisp linear programming model which can be rapidly solved by the Simplex algorithm. Finally, we employ this approach on a real-world fuzzy APP problem in an automobile pressing company. The results demonstrate the effectiveness and applicability of the proposed algorithm.

关键词： fuzzy set credibility theory aggregate production planning fuzzy programming

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