Chromosome Mutation vs. Gene Mutation in Evolutive Approaches for Solving the Resource-Constrained Project Scheduling Problem (RCPSP)

Abstract

Resource-Constrained Project Scheduling Problems (RCPSP) are some of the most important scheduling problems due to their applicability to real problems and their combinatorial complexity (NP-hard). In the literature, it has been shown that metaheuristic algorithms are the main option to deal with real-size problems. Among them, population-based algorithms, especially genetic algorithms, stand out for being able to achieve the best near-optimal solutions in reasonable computational time. One of the main components of metaheuristic algorithms is the solution representation (codification) since all search strategies are implemented based on it. However, most codings are affected by generating redundant solutions, which obstruct incorporating new information. In this paper, we focus on the study of the mutation operator (responsible for diversity in the population), in order to determine how to implement this operator to reduce the obtaining of redundant solutions. The computational assessment was done on the well-known PSPLIB library and shows that the proposed algorithm reaches competitive solutions compared with the best-proposed algorithms in the literature.