Finding a hybrid genetic algorithm-constraint satisfaction problem based solution for resource constrained project scheduling

Project scheduling has attracted many researchers in recent years. It is about single-item or small batch production where scarce resources have to be met when scheduling dependent activities over time. Because of high complexity of the problem uninformed search strategies cannot solve the problem optimally. This paper proposes a new evolutionary approach to resource constrained project scheduling problem. Hybrid genetic algorithm (GA)-constraint satisfaction problem (CSP) has been applied to solve resource constrained project scheduling (RCPS). GA's task is to find the best schedule. Discussed approach has used CSP in order to overcome the existing inconsistencies in activities precedence and resources conflicts. A full state CSP with min-conflict heuristic has been used for solving precedence conflicts. And a simple iterative CSP is used to resolve the resource conflicts.