21 research outputs found

    Nonsmooth multiobjective optimization using limiting subdifferentials

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    AbstractIn this study, using the properties of limiting subdifferentials in nonsmooth analysis and regarding a separation theorem, some weak Pareto-optimality (necessary and sufficient) conditions for nonsmooth multiobjective optimization problems are proved

    Optimal and strongly optimal solutions for linear programming models with variable parameters

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    AbstractThis paper deals with linear programming (LP) models with variable parameters and introduces two concepts for this class of problems: optimal solution and strongly optimal solution. Also, it seeks necessary and sufficient conditions for a feasible solution to be optimal or strongly optimal

    The cost and income efficiency models with MOLP structure

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    In this paper, the cost and income efficiency models have been considered with regard to the multiple objective programming structures. For finding the efficient points in purposed MOLP problem, some various methods like Lexicography & the weighted sum can be used. So by introducing the MOLP problem the cost & income efficiencies will be achieved. In the present study, the MOLP problem is converted to an objective function by the weighted sum of the objective function. So we determine the efficient hyperplanes gradient by finding the dual linear programming (LP) problem

    Finding strong defining hyperplanes of PPS using multiplier form

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    The production possibility set (PPS) is defined as the set of all inputs and outputs of a system in which inputs can produce outputs. In this paper, we deal with the problem of finding the strong defining hyperplanes of the PPS. These hyperplanes are equations that form efficient surfaces. It is well known that the optimal solutions of the envelopment formulation for extreme efficient units are often highly degenerate and, therefore, may have alternate optima for the multiplier form. Every optimal solution of the multiplier form yields a hyperplane which is supporting at the PPS. We will show that the hyperplane which corresponds to an extreme optimal solution of the multiplier form (in evaluating an efficient DMU), and whose components corresponding to inputs and outputs are non zero is a strong defining hyperplane of the PPS. This will be discussed in details in this paper. These hyperplanes are useful in sensitivity and stability analysis, the status of returns to scale of a DMU, incorporating performance into the efficient frontier analysis, and so on. Using numerical examples, we will demonstrate how to use the results.Data envelopment analysis Production possibility set Multiplier form

    A new method for measuring congestion in data envelopment analysis

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    In data envelopment analysis (DEA), there are two principal methods for identifying and measuring congestion: Those of Färe et al. [Färe R, Grosskopf S. When can slacks be used to identify congestion. An answer to W. W. Cooper, L. Seiford, J. Zhu. Socio-Economic Planning Sciences 2001;35:1-10] and Cooper et al. [Cooper WW, Deng H, Huang ZM, Li SX. A one-model approach to congestion in data envelopment analysis. Socio-Economic Planning Sciences 2002;36:231-8]. In the present paper, we focus on the latter work in proposing a new method that requires considerably less computation. Then, by proving a selected theorem, we show that our proposed methodology is indeed equivalent to that of Cooper et al.Data envelopment analysis Congestion Linear programming Efficiency Decision-making unit (DMU)
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