In most real-world situations for transportation planning decision (TPD) problems, environmental coefficients and parameters are imprecise/fuzzy in nature, and the decision maker (DM) generally faces a multi-objective...
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In most real-world situations for transportation planning decision (TPD) problems, environmental coefficients and parameters are imprecise/fuzzy in nature, and the decision maker (DM) generally faces a multi-objective TPD problem in a fuzzy environment. This work develops an interactive fuzzylinearprogramming (FLP) method for solving TPD problems with fuzzy goals, available supply and forecast demand. The proposed method attempts simultaneously to minimize the total production and transportation costs and the total delivery time with reference to available supply, machine capacities and budget constraints at each source, as well as forecast demand and warehouse space constraints at each destination. In addition, the proposed method provides a systematic framework that facilitates the DM interactively to modify the imprecise data and related parameters until a satisfactory solution is derived. An industrial case is used to demonstrate the feasibility of applying the proposed method to real-world TPD problems. Especially, several significant characteristics of the proposed FLP method are presented in contrast to those of the main TPD methods.
This work applies fuzzy sets to integrating manufacturing/distribution planning decision (MDPD) problems with multi-product and multi-time period in supply chains by considering time value of money for each of the ope...
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This work applies fuzzy sets to integrating manufacturing/distribution planning decision (MDPD) problems with multi-product and multi-time period in supply chains by considering time value of money for each of the operating cost categories. The proposed fuzzy multi-objective linear programming model (FMOLP) attempts to simultaneously minimize total costs and total delivery time with reference to inventory levels, available machine capacity and labor levels at each source, as well as market demand and available warehouse space at each destination, and the constraint oil total budget. An industrial case demonstrates the feasibility of applying the proposed model to a realistic MDPD problem and several significant management implications are presented based oil computational analysis and comparisons with the existing MDPD methods. The main advantage of the proposed model is that it presents a systematic framework that facilitates fuzzy decision-making for solving the multi-objective MDPD problems with multi-product and multi-time period in supply chains under all uncertain environment, enabling the decision maker to adjust the search direction during the solution procedure to obtain a preferred satisfactory solution. (C) 2008 Elsevier Ltd. All rights reserved.
This study develops a fuzzy multi-objective linear programming (FMOLP) model for solving the multi-product aggregate production planning (APP) decision problem in a fuzzy environment. The proposed model attempts to mi...
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This study develops a fuzzy multi-objective linear programming (FMOLP) model for solving the multi-product aggregate production planning (APP) decision problem in a fuzzy environment. The proposed model attempts to minimize total production costs, carrying and backordering costs and rates of changes in labor levels considering inventory level, labor levels, capacity, warehouse space and the time value of money. A numerical example demonstrates the feasibility of applying the proposed model to APP problem. Its advantages are also discussed. The proposed model yields a compromise solution and the decision maker's overall levels of satisfaction. In particular, in contrast to other APP models, several significant characteristics of the proposed model are presented. (C) 2003 Elsevier Ltd. All rights reserved.
This work presents a novel fuzzy multi-objective linear programming (f-MOLP) model for solving integrated production-transportation planning decision (PTPD) problems in supply chains in a fuzzy environment. The propos...
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This work presents a novel fuzzy multi-objective linear programming (f-MOLP) model for solving integrated production-transportation planning decision (PTPD) problems in supply chains in a fuzzy environment. The proposed model attempts to simultaneously minimise total production and transportation costs, total number of rejected items, and total delivery time with reference to available capacities, labor level, quota flexibility, and budget constraints at each source, as well as forecast demand and warehouse space at each destination. An industrial case demonstrates that the proposed f-MOLP model achieves an efficient compromise solution and overall decision maker satisfaction with determined goal values. Additionally, the proposed model provides a systematic framework that facilitates decision makers to interactively modify the fuzzy data and parameters until a satisfactory solution is obtained. Overall, the f-MOLP model offers a practical method for solving PTPD problems with fuzzymultiple goals, and can effectively improve producer-distributor relationships within a supply chain.
This work develops a fuzzy multi-objective linear programming (FMOLP) model with piecewise linear membership function to solve integrated multi-product and multi-time period production/distribution planning decisions ...
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This work develops a fuzzy multi-objective linear programming (FMOLP) model with piecewise linear membership function to solve integrated multi-product and multi-time period production/distribution planning decisions (PDPD) problems with fuzzyobjectives. The original multi-objectivelinearprogramming designed in this work model attempts to simultaneously minimize total costs and total delivery time in relation to inventory levels, available machine capacity and labor levels at each Source, and forecast demand and available warehouse space at each destination and total budget. The proposed FMOLP model provides a systematic framework that facilitates fuzzy decision-making process, enabling the decision maker (DM) to interactively adjust the search direction during the solution procedure to obtain a DM's preferred satisfactory solution. Additionally, the DM computes the value in each cost category by considering the time value of money in the proposed model, which is appropriate for practical application to the PDPD problem in a supply chain. Finally, an industrial case demonstrates the feasibility of applying the proposed model to a real-world integrated PDPD problem in a supply chain under uncertain
A method is proposed for solving a fuzzy multi-objective linear programming problem (FMP) with quasiconcave membership functions and fuzzy coefficients. The proposed method first expresses a piecewise function as the ...
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A method is proposed for solving a fuzzy multi-objective linear programming problem (FMP) with quasiconcave membership functions and fuzzy coefficients. The proposed method first expresses a piecewise function as the summation of absolute terms. Then we search for the interval where the optimal solution is allocated by finding the corresponding points with same value of membership functions. After that, the problem is solved by goal programming techniques. Comparing with other FMP methods, the proposed method does not need to add extra zero-one variables, to divide the original problem into several sub-problems, or transforming all original quasiconcave functions into concave functions. In addition, the proposed method could solve a FMP problem with fuzzy coefficients;to obtain a solution closing to a global optimum. (C) 2000 Elsevier Science B.V. All rights reserved.
Taipower, the official electricity authority of Taiwan, encounters several difficulties in planning annual coal purchase and allocation schedule, e.g., with multiple sources, multiple destinations, multiple coal types...
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Taipower, the official electricity authority of Taiwan, encounters several difficulties in planning annual coal purchase and allocation schedule, e.g., with multiple sources, multiple destinations, multiple coal types, different shipping vessels, and even in uncertain demand and supply. In this study, these concerns are formulated as a fuzzy bicriteria multi-index transportation problem. Furthermore, an effective and interactive algorithm is proposed which combines reducing index method and interactive fuzzy multi-objective linear programming technique to cope with a complicated problem which may be prevalent in other industries. Results obtained in this study clearly demonstrate that this model can not only satisfy more of the actual requirements of the integral system but also offer more information to the decision makers (DMs) for reference in favor of exalting decision making quality.
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