We show by counterexample that one of the results in the paper "On Pareto optima, the Fermat-Weber problem, and polyhedral gauges", by R. Durier, Mathematical programming 47 (1990), does not hold. The stated...
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We show by counterexample that one of the results in the paper "On Pareto optima, the Fermat-Weber problem, and polyhedral gauges", by R. Durier, Mathematical programming 47 (1990), does not hold. The stated characterization of properly efficient points for a scalar location problem is only true in dimension 1 and 2. For higher dimensions, the property stated is necessary, but not sufficient.
We present a method of obtaining some classes of generalized V-univex type-I multiobjective optimization problems starting from classes of problems involving functions defined on R". In this way, examples of mult...
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ISBN:
(纸本)9789955282839
We present a method of obtaining some classes of generalized V-univex type-I multiobjective optimization problems starting from classes of problems involving functions defined on R". In this way, examples of multiobjective optimization problems given in previous articles, which are mentioned in the references, can be reformulated as optimization problems with generalized vectorial functions and having the same properties as the original ones.
Rural-urban land conversion is an inevitable phenomenon in urbanization arid industrialization. And the decision-making issue about this conversion is multi-objective because the social decision maker （the whole of c...
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Rural-urban land conversion is an inevitable phenomenon in urbanization arid industrialization. And the decision-making issue about this conversion is multi-objective because the social decision maker （the whole of central government and local authority） has to integrate the requirements of different interest groups （rural collective economic organizations, peasants, urban land users and the ones affected indirectly） and harmonize the sub-objects （economic, social and ecological outcomes） of this land allocation process. This paper established a multi-objective programming model for rural-urban land conversion decision-making and made some social welfare analysis correspondingly. Result shows that the general object of rural-urban land conversion decision-making is to reach the optimal level of social welfare in a certain state of resources allocation, while the preference of social decision makers and the value judgment of interest groups are two crucial factors which determine the realization of the rural-urban land conversion decision-making objects.
In this present article we have given some multiobjective programming problems with their symmetric duals and have derived weak and strong duality results with respect to such programs. Moreover, we have also used mos...
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In this present article we have given some multiobjective programming problems with their symmetric duals and have derived weak and strong duality results with respect to such programs. Moreover, we have also used most general type of invexity assumptions involved with the functions which are related to the programming problems. It is to be pointed out that the objective functions in such programs contain terms like support functions which in turn are able to give results on particular classes of programs involving quadratic terms. Our results in particular give as special cases some earlier results on symmetric duals given in the current literature. (c) 2004 Published by Elsevier B.V.
A weight assessing method is given for solving a multiple attribute decision problem involving one decision maker. The method provides significant freedom to the decision maker who is asked only to specify certain gro...
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A weight assessing method is given for solving a multiple attribute decision problem involving one decision maker. The method provides significant freedom to the decision maker who is asked only to specify certain groups of attributes and the corresponding joint weights. The method then provides a sophisticated interaction between various levels of the attributes involved. Furthermore, if the decision maker wishes to give additional information of the above-mentioned kind, he establishes an interaction on the level of the solution process. This can compensate for the inherent limitations of any method based on scalar utility functions by allowing a certain intransitivity and incomparability of preferences, which are natural in multiple attribute situations. [ABSTRACT FROM AUTHOR]
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.
This study addresses a fundamental difficulty in designing cellular manufacturing (CM) systems, the cell formation problem. This problem has its strategic importance in that it affects the fundamental structure and ov...
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This study addresses a fundamental difficulty in designing cellular manufacturing (CM) systems, the cell formation problem. This problem has its strategic importance in that it affects the fundamental structure and overall layout of a CM system. A heuristic model is developed which assigns parts and machines to manufacturing cells while taking into account machine capacities, product routings, relevant costs, and several objectives of production systems. A full factorial experimental design is used to evaluate the effects of environmental factors on the performance of the heuristic model. Large cell formation problems are solved with the heuristic model to further characterize the model with respect to solution characteristics and computer run time.
Purchases from vendors involve significant costs for many firms. Decisions related to these purchases include the selection of vendors and the determination of order quantities to be placed with the selected vendors. ...
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Purchases from vendors involve significant costs for many firms. Decisions related to these purchases include the selection of vendors and the determination of order quantities to be placed with the selected vendors. Such decisions are frequently multiobjective in nature. That is, they are evaluated by more than one criterion. At least 23 criteria for various vendor selection problems have been identified. In this article, we present a multiobjective approach to systematically analyze the inherent tradeoffs involved in multicriteria vendor selection problems. The approach is motivated by, and demonstrated with, an actual purchasing problem facing a division of a Fortune 500 company.
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.
In stratified sampling when strata weights are unknown a double sampling technique may be used to estimate them. A large simple random sample from the unstratified population is drawn and units falling in each stratum...
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In stratified sampling when strata weights are unknown a double sampling technique may be used to estimate them. A large simple random sample from the unstratified population is drawn and units falling in each stratum are recorded. A stratified random sample is then selected and simple random subsamples are obtained out of the previously selected units of the strata. This procedure is called double sampling for stratification. If the problem of non-response is there, then subsamples are divided into classes of respondents and non-respondents. A second subsample is then obtained out of the non-respondents and an attempt is made to obtain the information by increasing efforts, persuasion and call backs. In this paper, the problem of obtaining a compromise allocation in multivariate stratified random sampling is discussed when strata weights are unknown and non-response is present. The problem turns out to be a multiobjective non-linear integer programming problem. An approximation of the problem to an integer linear programming problem by linearizing the non-linear objective functions at their individual optima is worked out. Chebyshev's goal programming technique is then used to solve the approximated problem. A numerical example is also presented to exhibit the practical application of the developed procedure.
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