Elitist Vector Evaluated Particle Swarm Optimization for Multi - mode Resource Leveling Problems ⋆

This paper focuses on solving a typical multi-mode resource leveling problem, in which activity duration depends on committed resources, project deadlines and other constraints. To solve this problem, we establish a multi-objective model to minimize project duration, resource requirements and resource variance. Based on the established model, a novel Elitist Vector Evaluated Particle Swarm Optimization (EVEPSO) is utilized for solving this problem. A set of experiments have been conducted based on EVEPSO method: and the empirical results indicate that EVEPSO can accurately and efficiently solve the multi-mode resource leveling problem. The computational results further suggest that project duration and minimum resource variance correlate negatively. However, there are few correlations between resource requirements and minimum resource variance.