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A new heuristic approach for the large-scale Generalized assignment problem

By S. Raja Balachandar

Abstract

and K.Kannan Abstract—This paper presents a heuristic approach to solve the Generalized Assignment Problem (GAP) which is NP-hard. It is worth mentioning that many researches used to develop algorithms for identifying the redundant constraints and variables in linear programming model. Some of the algorithms are presented using intercept matrix of the constraints to identify redundant constraints and variables prior to the start of the solution process. Here a new heuristic approach based on the dominance property of the intercept matrix to find optimal or near optimal solution of the GAP is proposed. In this heuristic, redundant variables of the GAP are identified by applying the dominance property of the intercept matrix repeatedly. This heuristic approach is tested for 90 benchmark problems of sizes upto 4000, taken from OR-library and the results are compared with optimum solutions. Computational complexity isprovedtobeO(mn) of solving GAP using this approach. The performance of our heuristic is compared with the best state-ofthe-art heuristic algorithms with respect to both the quality of the solutions. The encouraging results especially for relatively large size test problems indicate that this heuristic approach can successfully be used for finding good solutions for highly constrained NP-hard problems

Topics: Generalized Assignment Problem, Intercept Matrix, Heuristic, Computational Complexity, NP-Hard Problems
Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.352.9812
Provided by: CiteSeerX
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