A new multi-objective algorithm for a project selection problem

Project selection problem is an incessant problem, which every organization face. It, in fact, plays a key role in prosperity of the company. Meta-heuristic methods are the well-reputed methods which have been employed to solve a variety of multi-objective problems forming the real world problems. In this paper, a new multi-objective algorithm for project selection problem is studied. Two objective functions have been considered to maximize total expected benefit of selected projects and minimize the summa-summation of the absolute variation of allotted resource between each successive time periods. A meta-heuristic multi-objective is proposed to obtain diverse locally non-dominated solutions. The proposed algorithm is compared, based on some prominent metrics, with a well-known genetic algorithm, i.e. NSGA-II. The computational results show the superiority of the proposed algorithm in comparison with NSGA-II. Crown Copyright (C) 2008 Published by Elsevier Ltd. All rights reserved.