A multiple criteria decision model for information system project selection
Computers and Operations Research
A multi-objective scatter search for a mixed-model assembly line sequencing problem
Advanced Engineering Informatics
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
A hybrid fuzzy rule-based multi-criteria framework for sustainable project portfolio selection
Information Sciences: an International Journal
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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 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.