Genetic Algorithm for Resource Leveling Problems under Various Objective Functions

Abstract

In this paper some resource leveling problems for project scheduling under resource constraints are considered. In this problem activities of a project are to be scheduled in a way that all precedence and resource constraints are satisfied, and a given objective function describing the fluctuations of resource usage is minimized. Activities are nonpreemptable, and resources are renewable. Several various objective functions for the problem are analyzed. A genetic algorithm is proposed to solve this strongly NP-hard problem. The performance of the algorithm is examined and compared to other simple heuristics on a basis of a computational experiment performed on a set of standard benchmark instances.