The vendor selection problem (VSP) is a critical element of the numerous managerial decisions in the consideration of both outsourcing and integrated supply chain management. Many papers in the literature have dealt w...
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The vendor selection problem (VSP) is a critical element of the numerous managerial decisions in the consideration of both outsourcing and integrated supply chain management. Many papers in the literature have dealt with VSPs from a multicriteria perspective, but few have looked into the implications of such decisions in a multiechelon supply chain with the explicit consideration of multiple time-phased demands. A new integrated supply chain model is proposed for a multiechelon supply chain. This model takes into account the usual cost objective and other important criteria in a multiechelon supply chain ranging from the most upstream suppliers' quality to end customers' satisfaction level through a large-scale multiobjectivelinear programme (MOLP). Furthermore, various Pareto optimal solutions can be graphically presented to facilitate decision making and negotiations with existing and potential suppliers.
Given a biobjective linearprogramming problem,we develop an affine scaling algorithm with min-max direction and demonstrate its convergence for an efficient *** implement the algorithm for some minor issues in the li...
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Given a biobjective linearprogramming problem,we develop an affine scaling algorithm with min-max direction and demonstrate its convergence for an efficient *** implement the algorithm for some minor issues in the literature.
This paper presents the results of an investigation into computational considerations that are relevant to large-scale multiobjective linear programming (MOLP) problems. Four approaches to obtaining a representation o...
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This paper presents the results of an investigation into computational considerations that are relevant to large-scale multiobjective linear programming (MOLP) problems. Four approaches to obtaining a representation of the ideal solution are compared. Statistics on the number of simplex iterations and CPU time required are analysed for a set of randomly generated multiobjective linear programming problems. Recommendations are made based on the analysis of these results which are applicable to many MOLP solution algorithms.
In this paper we present a weak duality theorem and a complementary slackness theorem, which were omitted from the duality theory of the Gale-Kuhn-Tucker matrix optimization problem. We also show that the results are ...
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In this paper we present a weak duality theorem and a complementary slackness theorem, which were omitted from the duality theory of the Gale-Kuhn-Tucker matrix optimization problem. We also show that the results are closely related to the duality of multiple-criteria and multiple-constraint level (MC2) programming and the duality of multiobjective linear programming respectively.
The aim of this note is to point out and correct some errors in the definitions, notations operations and possibilistic programming model introduced by Sadi-Nezhad and Akhtari (2008) and hereby develop two correct pos...
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The aim of this note is to point out and correct some errors in the definitions, notations operations and possibilistic programming model introduced by Sadi-Nezhad and Akhtari (2008) and hereby develop two correct possibilistic programming models for fuzzy multidimensional analysis of preference in the fuzzy multiattribute group decision making problems with both the fuzzy weight vector and the fuzzy positive ideal solution (PIS) unknown a priori. (C) 2014 Elsevier Ltd. All rights reserved.
This article describes LUSE, a system for exploration of rural land use allocations (total area devoted to each kind of use) by multiobjective linear programming methods. The objectives pursued are maximization of gro...
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This article describes LUSE, a system for exploration of rural land use allocations (total area devoted to each kind of use) by multiobjective linear programming methods. The objectives pursued are maximization of gross margin, employment in agriculture, land use naturalness and traditional rural landscape, and minimization of production costs and use of agrochemicals. The constraints oil the areas devoted to the land uses considered in addition to those imposed by their joint and individual availabilities, are that they must reach levels considered to satisfy existing demand for those uses or their products, and that the areas devoted to maize and fodder must be sufficient for maintenance of dairy farm production. The program generates comprehensive samples of the Pareto-optimal set, and also allows interactive convergence on a solution that is satisfactory to the decision-maker or interactive exploration of the Paretooptimal set. The system is currently parameterized for use in an area of Galicia (N.W. Spain), but is easily adaptable to other geographic locations. (C) 2006 Elsevier Ltd. All rights reserved.
Forest management planning is a joint process of decision synthesis and tradeoff analysis. We present an interactive method of multi-objective linearprogramming for supporting the planning process. In the proposed pr...
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Forest management planning is a joint process of decision synthesis and tradeoff analysis. We present an interactive method of multi-objective linearprogramming for supporting the planning process. In the proposed procedure, emphasis is placed on reducing uncertainty that surrounds the resolution of goal conflicts. Parametric analysis is iteratively performed to shed insights into the question of what happens to goal tradeoffs if a particular criterion is achieved at alternative levels. The composite objective function guiding the parametric analysis is updated as decision maker replaces a previous choice with an improved one. Central to this step is the induction of criterion weights implied by a decision instance, through the use of shadow prices. Finally, ordinal goal priority is employed to generate initial solution and decompose a multi-objective planning problem into more tractable subproblems. The interactive procedure is illustrated by a land-use planning model containing five forest-related outputs, including noncommercial grazing, commercial grazing, timber, camping, and profit.
Flux balance analysis (FBA) is well acknowledged as an analysis tool of metabolic networks in the framework of metabolic engineering. However, FBA has a limitation for solving a multiobjective optimization problem whi...
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Flux balance analysis (FBA) is well acknowledged as an analysis tool of metabolic networks in the framework of metabolic engineering. However, FBA has a limitation for solving a multiobjective optimization problem which considers multiple conflicting objectives. In this study, we propose a novel multiobjective flux balance analysis method, which adapts the noninferior set estimation (NISE) method (Solanki et al., 1993) for multiobjective linear programming (MOLP) problems. NISE method can generate an approximation of the Pareto curve for conflicting objectives without redundant iterations of single objective optimization. Furthermore, the flux distributions at each Pareto optimal solution can be obtained for understanding the internal flux changes in the metabolic network. The functionality of this approach is shown by applying it to a genome-scale in silico model of E. coli. Multiple objectives for the poly(3-hydroxybutyrate) [P(3HB)] production are considered simultaneously, and relationships among them are identified. The Pareto curve for maximizing succinic acid production vs. maximizing biomass production is used for the in silico analysis of various combinatorial knockout strains. This proposed method accelerates the strain improvement in the metabolic engineering by reducing computation time of obtaining the Pareto curve and analysis time of flux distribution at each Pareto optimal solution. 0 2009 American Institute of Chemical Engineers Biotechnol. Prog., 25: 999-1008, 2009
In this paper we propose an evolutionary algorithm to estimate the minimum (nadir) objective values over the efficient set in multiple objective linearprogramming problems (MOLP). Nadir values provide valuable inform...
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ISBN:
(纸本)9783642010194
In this paper we propose an evolutionary algorithm to estimate the minimum (nadir) objective values over the efficient set in multiple objective linearprogramming problems (MOLP). Nadir values provide valuable information for characterizing the ranges of the objective function values over the efficient set. However, they are very hard to compute in the general case. The proposed algorithm uses a population of weight vectors with particular characteristics, which are then used as parameters in the optimization of weighted-sums of the objective functions. The population evolves through a process of selection, recombination and mutation. The algorithm has been tested on a number of random MOLP problems for which the nadir point is known. A result comparison with an exact method is shown and discussed.
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