We propose models to investigate effectiveness-equity tradeoffs in tree network facility location problems. We use the commonly used median objective as a measure of effectiveness, and the Gini index as a measure of (...
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We propose models to investigate effectiveness-equity tradeoffs in tree network facility location problems. We use the commonly used median objective as a measure of effectiveness, and the Gini index as a measure of (in)equity, and formulate bicriteria problems involving these objectives. We develop procedures to identify an efficient set of solutions to these problems, analyze the complexity of the proposed procedures, and finally illustrate the procedures with an *** (c) 2012 Wiley Periodicals, Inc. NETWORKS, Vol. 62(4), 243-254 2013
In this paper, we propose a credibilistic framework for portfolio selection problem using an expected value multiobjective model with fuzzy parameters. We consider short term return, long term return, risk and liquidi...
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In this paper, we propose a credibilistic framework for portfolio selection problem using an expected value multiobjective model with fuzzy parameters. We consider short term return, long term return, risk and liquidity as key financial criteria. A solution procedure comprising fuzzy goal programming and fuzzy simulation based real-coded genetic algorithm is developed to solve the model. The proposed solution approach is considered advantageous particularly for the cases where the fuzzy parameters of the problem may assume any general functional form. An empirical study is included to illustrate the usefulness of the proposed model and solution approach in real-world applications of portfolio selection.
In this paper we develop a multicriteria credibilistic framework for portfolio rebalancing. We use an expected value model with fuzzy parameters considering return, risk and liquidity as key financial criteria. The tr...
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In this paper we develop a multicriteria credibilistic framework for portfolio rebalancing. We use an expected value model with fuzzy parameters considering return, risk and liquidity as key financial criteria. The transaction costs are assumed to be paid on the basis of incremental discounts and are adjusted in the net return of the portfolio. A solution procedure based on fuzzy goal programming and a hybrid intelligent algorithm that combines fuzzy simulation with a real-coded genetic algorithm is presented to solve the portfolio rebalancing problem. The approach adopted here has the advantage of handling the multicriteria portfolio rebalancing problem where the fuzzy parameters are characterized by general functional forms. An empirical study is included to demonstrate the effectiveness of the solution approach and efficiency of the model in practical applications of rebalancing an existing portfolio. (c) 2012 Elsevier B.V. All rights reserved.
In this paper, new classes of generalized type I functions are introduced by combining the concepts of B - (p, r, a)-invex function and generalized type I function. several optimality sufficient conditions are obtaine...
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ISBN:
(纸本)9781479925483
In this paper, new classes of generalized type I functions are introduced by combining the concepts of B - (p, r, a)-invex function and generalized type I function. several optimality sufficient conditions are obtained for multi- objective programming under weaker convexity.
This paper considers linear programming problems where objective functions involve fuzzy random variables. New decision making models, called possibilistic mean model, are proposed in order to maximize the mean (expec...
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ISBN:
(纸本)9781479906529
This paper considers linear programming problems where objective functions involve fuzzy random variables. New decision making models, called possibilistic mean model, are proposed in order to maximize the mean (expectation) of the degrees of possibility and necessity with respect to attained objective function values. It is shown that the original fuzzy random programming problems are transformed into deterministic nonlinear ones which can be solved by conventional nonlinear programming techniques.
Taking No.11 flue gas desulfurization (FGD) site in Taiyuan Second Thermal Power Plant (TSTPP) as an example, the authors respectively deduced the models of technical performance indexes including SO2 removal efficien...
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ISBN:
(纸本)9783037856499
Taking No.11 flue gas desulfurization (FGD) site in Taiyuan Second Thermal Power Plant (TSTPP) as an example, the authors respectively deduced the models of technical performance indexes including SO2 removal efficiency and outlet SO2 concentration and the models of economical performance indexes including limestone consumption, power consumption and process water consumption. Then, by using the least square linear and nonlinear regression method, the authors obtained the practical mathematic models in the period of 21:00, Mar. 28th and 3:00, Mar. 29th, 2007. Finally, the authors calculated the optimal solutions of slurry pH value, calcium-sulfur (Ca/S) mole ratio and liquid-gas (L/G) ratio by utilizing the multiobjective programming method. Using this method, the desulfurization system works safely and economically.
To remedy challenges resulting from a high number of objectives in multiobjective programming and multicriteria decision making, this paper chooses to decompose the vector objective function and characterizes the rela...
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To remedy challenges resulting from a high number of objectives in multiobjective programming and multicriteria decision making, this paper chooses to decompose the vector objective function and characterizes the relationships between solutions for the original problem and the collection of decomposed subproblems. In particular, it is shown how solutions that are found using this decomposition approach relate to solutions found by traditional scalarization techniques. For the selection of a final solution, two interactive coordination methods are proposed that allow to find any solution for the original problem by merely solving the smaller-sized subproblems, while integrating both preferences of the decision maker and trade-off information obtained from a sensitivity analysis. A theoretical foundation for the procedures is established, and their application is illustrated for portfolio optimization and a design selection problem.
In this paper, we revisit one of the most important scalarization techniques used in multiobjective programming, the epsilon-constraint method. We summarize the method and point out some weaknesses, namely the lack of...
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In this paper, we revisit one of the most important scalarization techniques used in multiobjective programming, the epsilon-constraint method. We summarize the method and point out some weaknesses, namely the lack of easy-to-check conditions for properly efficient solutions and the inflexibility of the constraints. We present two modifications that address these weaknesses by first including slack variables in the formulation and second elasticizing the constraints and including surplus variables. We prove results on (weakly, properly) efficient solutions. The improved epsilon-constraint method that we propose combines both modifications.
In this paper, we introduce new classes of vector functions which generalize the class of scalar invex functions. We prove that these new classes of vector functions are characterized in such a way that every vector c...
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In this paper, we introduce new classes of vector functions which generalize the class of scalar invex functions. We prove that these new classes of vector functions are characterized in such a way that every vector critical point is an efficient solution of a multiobjective programming Problem. We establish relationships between these new classes of functions and others used in the study of efficient and weakly efficient solutions. (C) 2008 Elsevier Ltd. All rights reserved.
In this paper by employing an asymptotic approach we develop an existence and stability theory for convex multiobjective programming. We deal with the set of weakly efficient minimizers. To this end we employ a notion...
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In this paper by employing an asymptotic approach we develop an existence and stability theory for convex multiobjective programming. We deal with the set of weakly efficient minimizers. To this end we employ a notion of convergence for vector-valued functions close to that due to Lemaire. (c) 2008 Elsevier B.V. All rights reserved.
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