1995•OptimizationRequires access

A Goal Programming Method for Solving Fractional Programming Problems via Dynamic Programming

B.B. Pal, I. Basu

Open publisher page 36 citations

Abstract

This paper presents a Goal Programming (GP) method to solve a class of Fractional Programming (FP) problems which have the characteristics of Dynamic Programming (DP) problems. The method is designed to solve the problems when one or more objective goals appear at the same priority level and the method works in such a way that the problem is solved recursively without linearizing the fractional objectives. In the solution process, the feasible regions of the decision variables are determined by using GP rather than the traditional DP method. An example is provided to illustrate the method outlined

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What this paper is about

This paper presents a Goal Programming (GP) method to solve a class of Fractional Programming (FP) problems which have the characteristics of Dynamic Programming (DP) problems. The method is designed to solve the problems when one or more objective goals appear at the same priority level and the method works in such a way that the problem is solved recursively without linearizing the fractional objectives. In the solution process, the feasible regions of the decision variables are determined by using GP rather than the traditional DP method. An example is provided to illustrate the method outlined

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OpenAlex reports 36 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper presents a Goal Programming (GP) method to solve a class of Fractional Programming (FP) problems which have the characteristics of Dynamic Programming (DP) problems. The method is designed to solve the problems when one or more objective goals appear at the same priority level and the method works in such a way that the problem is solved recursively without linearizing the fractional objectives. In the solution process, the feasible regions of the decision variables are determined by using GP rather than the traditional DP method. An example is provided to illustrate the method outlined

Key concepts: Fractional programming, Mathematical optimization, Goal programming, Mathematics, Constraint programming, Class (philosophy), Dynamic programming, Linear-fractional programming

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