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 membershi...
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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.
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 f...
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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.
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 ...
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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.
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 enterpr...
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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.
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 pr...
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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.
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 c...
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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.
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...
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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.
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 cert...
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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.
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...
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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.
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 custom...
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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.
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