%0 Journal Article
	%A Fatemeh Azimi and  Razeeh Sadat Aboutalebi and  Amir Abbas Najafi
	%D 2011
	%J International Journal of Industrial and Manufacturing Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 54, 2011
	%T Using Multi-Objective Particle Swarm Optimization for Bi-objective Multi-Mode Resource-Constrained Project Scheduling Problem
	%U https://publications.waset.org/pdf/12270
	%V 54
	%X In this paper the multi-mode resource-constrained project scheduling problem with discounted cash flows is considered. Minimizing the makespan and maximization the net present value (NPV) are the two common objectives that have been investigated in the literature. We apply one evolutionary algorithm named multiobjective particle swarm optimization (MOPSO) to find Pareto front solutions. We used standard sets of instances from the project scheduling problem library (PSPLIB). The results are computationally compared respect to different metrics taken from the literature on evolutionary multi-objective optimization.

	%P 1015 - 1019