Scheduling Multi-objective IT Projects and Human Resource Allocation by NSVEPSO

Abstract

In any information technology enterprise, resource allocation and project scheduling are two important issues to reduce project duration, cost and risk in multi-project environments. This paper proposes an integrated and efficient computational method based on multi-objective particle swarm optimization to solve these two interdependent problems simultaneously. Minimizing the project duration, cost and maximizing the quality of resource allocation are all considered in our approach. Moreover, we suggest a novel non-dominated sorting vector evaluated particle swarm optimization (NSVEPSO). In order to improve its efficiency, this algorithm first uses a novel method for setting the global best position, and then executes a non-dominated sorting process to select new population. The performance of NSVEPSO is evaluated by comparison with SWTC_NSPSO, VEPSO and NSGA-III. The results of four experiments in the real scenario with small, medium and large data sizes show that NSVEPSO provides better boundary solutions and costs less time than the other algorithms.