An efficient solution to biobjective generalized assignment problem

The generalized assignment problem (GAP) has found applications in many real world problems. In this paper, we examine the GAP from a multiobjective point of view to accommodate some real world situations where more than one objective is involved. An efficient LP-based heuristic is proposed to solve the biobjective generalized assignment problem (BiGAP). Extensive computational experiments are carried out to evaluate the performance of the proposed method. The results show that the proposed approach is able to generate good approximations to the nondominated frontier of the BiGAP efficiently, especially when the ratio of the number of items to the number of knapsacks is large.