The multicriteria Bipolar method can be extended and used to control multicriteria, multistage decision processes. In this extension, at each stage of the given multistage process two sets of reference points are dete...
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The multicriteria Bipolar method can be extended and used to control multicriteria, multistage decision processes. In this extension, at each stage of the given multistage process two sets of reference points are determined, constituting a reference system for the evaluation of stage alternatives. Multistage alternatives, which are compositions of stage alternatives, are assigned to one of six predefined hierarchical classes and then ranked. The aim of this paper is to show the possibility of finding the best multistage alternative, using Bellman's optimality principle and optimality equations. Of particular importance is a theorem on the non-dominance of the best multistage alternative, proven here. The methodology proposed allows to avoid reviewing each multistage alternative, which is important in large-size problems. The method is illustrated by a numerical example and a brief description of the sustainable regional development problem. The problem can be solved by means of the proposed procedure.
We consider a stochastic discrete multiobjectiveprogramming process with a finite number of stages. The number of states at each stage and the number of feasible decisions at each state are also finite. The aim of th...
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We consider a stochastic discrete multiobjectiveprogramming process with a finite number of stages. The number of states at each stage and the number of feasible decisions at each state are also finite. The aim of the paper is to propose a new interactive procedure for such a problem based on trade-off analysis. The procedure is illustrated with project portfolio selection. There are many organizations with moderately large portfolios of projects. Although the problem under discussion is not very large, it is difficult to solve, since projects are not implemented simultaneously. Moreover, the companies must take into account the risk that a particular project, which is planned to start in the future, may not be ready for implementation. We present an interactive trade-off procedure, based on the stochastic approach, as a new proposition to solve such a problem.
When analyzing multiple objective, multiperiod decision processes it is worth while to describe relations among objectives considered in consecutive periods and objectives for the whole process. The aim of the paper i...
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ISBN:
(纸本)9789616165303
When analyzing multiple objective, multiperiod decision processes it is worth while to describe relations among objectives considered in consecutive periods and objectives for the whole process. The aim of the paper is to describe a situation in which period objectives have changeable importance in consecutive periods. The problem of a-importance of period objectives is formulated and definitions of the importance function for the considered process and of a-efficient realizations are given. Relations between sets of efficient solutions and a-efficient solutions are analyzed, and some decision recommendations are given. Numerical examples are also presented.
Multiple objectives and dynamics characterize many sequential decision problems. In the paper we consider returns in partially ordered criteria space as a way of generalization of single criterion dynamicprogramming ...
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Multiple objectives and dynamics characterize many sequential decision problems. In the paper we consider returns in partially ordered criteria space as a way of generalization of single criterion dynamicprogramming models to multiobjective case. In our problem evaluations of alternatives with respect to criteria are represented by distribution functions. Thus, the overall comparison of two alternatives is equivalent to the comparison of two vectors of probability distributions. We assume that the decision maker tries to find a solution preferred to all other solutions (the most preferred solution). In the paper a new interactive procedure for stochastic, dynamic multiple criteria decision making problem is proposed. The procedure consists of two steps. First, the Bellman principle is used to identify the set of efficient solutions. Next interactive approach is employed to find the most preferred solution. A numerical example and a real-world application are presented to illustrate the applicability of the proposed technique.
An efficient numerical solution scheme entitled adaptive differential dynamicprogramming is developed in this paper for multiobjective optimal control problems with a general separable structure. For a multiobjective...
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An efficient numerical solution scheme entitled adaptive differential dynamicprogramming is developed in this paper for multiobjective optimal control problems with a general separable structure. For a multiobjective control problem with a general separable structure, the "optimal" weighting coefficients for various performance indices are time-varying as the system evolves along any noninferior trajectory. Recognizing this prominent feature in multiobjective control, the proposed adaptive differential dynamicprogramming methodology combines a search process to identify an optimal time-varying weighting sequence with the solution concept in the conventional differential dynamicprogramming. Convergence of the proposed adaptive differential dynamicprogramming methodology is addressed. (C) 2002 Elsevier Science Ltd. All rights reserved.
This paper presents an algorithm for generating efficient solutions of multiobjective mathematical programming problem. The generation of efficient solutions is based on the principle of optimality in dynamic programm...
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This paper presents an algorithm for generating efficient solutions of multiobjective mathematical programming problem. The generation of efficient solutions is based on the principle of optimality in dynamicprogramming. A generalized functional equation of dynamicprogramming is derived from the constraint method assuming the separability and monotonicity of the problem. The basic notion of stability in convex programming problems with parameters in the constraints is redefined and analyzed quantitatively for the problem. A numerical example is given for the sake of illustration.
This paper presents an algorithm for decomposing the parametric space in multiobjective dynamic programming (MODP) problems by using the weighted norm approach. Also, the basic notions of stability in convex programmi...
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This paper presents an algorithm for decomposing the parametric space in multiobjective dynamic programming (MODP) problems by using the weighted norm approach. Also, the basic notions of stability in convex programming problems with parameters in the objective functions are redefined and analyzed qualitatively for MODP problems. A numerical example is given to clarify the developed algorithm.
The case study presented in this paper has been developed after several years of spreadsheet-based model and trial and error analysis for game management in Southern Spain. The experience gained in this applied planni...
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The case study presented in this paper has been developed after several years of spreadsheet-based model and trial and error analysis for game management in Southern Spain. The experience gained in this applied planning permitted the authors to make a model for the average manager's criteria. This research proves that management models can be improved by using multicriteria approaches, especially when a satisfactory combination of methods is employed. First, an efficient set is generated for analysing the conflict between economic and ecological objectives. Second, a lexicographical GP model obtains the management plan.
In this paper, a method of generating efficient solutions of multiobjectiveprogramming problems is considered. This method is based on the principle of optimality in dynamicprogramming and fuzzy decision approach (h...
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In this paper, a method of generating efficient solutions of multiobjectiveprogramming problems is considered. This method is based on the principle of optimality in dynamicprogramming and fuzzy decision approach (hybrid approach). Also, this paper shows that solutions obtained by this approach are always efficient solutions. A numerical example is given for the sake of illustration.
A general class of nonseparable dynamic problems is studied in a dynamicprogramming framework by introducingkth-order separability. The solution approach uses multiobjective dynamic programming as a separation strate...
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A general class of nonseparable dynamic problems is studied in a dynamicprogramming framework by introducingkth-order separability. The solution approach uses multiobjective dynamic programming as a separation strategy forkth-order separable dynamic problems. The theoretical grounding on which the optimal solution of the original nonseparable dynamic problem can be attained by a noninferior solution of the corresponding multiobjective dynamic programming problem is established. The relationship between the overall optimal Lagrangian multipliers and the stage-optimal Lagrangian multipliers and the relationship between the overall weighting vector and the stage weighting vector are explored, providing the basis for identifying the optimal solution of the original nonseparable problem from among the set of noninferior solutions generated by the envelope approach.
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