AN EXACT METHOD TO SOLVE THE MULTI-OBJECTIVE ASSIGNMENT PROBLEM

ABSTRACT In this paper, we present a branch and bound-based technique for generating the nondominated set for the multi-objective assignment problem. The approach utilizes the Hungarian algorithm to solve a single-objective assignment problem at each node of the search tree. It then selects the set of candidate variables based on the descent directions of the objective functions, which enables the triggering of the branching process. The algorithm is enhanced with fathoming rules to expedite the convergence of the method. Computational experiments were conducted on a large number of instances, considering more than three objectives. These experiments demonstrate the effectiveness of the method and its competitiveness when compared to previous works.