BPGA-EDA for the multi-mode resource constrained project scheduling problem.
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AYODELE, M., MCCALL, J. and REGNIER-COUDERT, O. 2016. BPGA-EDA for the multi-mode resource constrained project scheduling problem. In the Proceedings of the IEEE congress on evolutionary computation (CEC), 24-29 July 2016, Vancouver, Canada. Piscataway, NJ: IEEE [online], pages 3417-3424. Available from: https://doi.org/10.1109/CEC.2016.7744222
The Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP) has been of research interest for over two decades. The problem is composed of two interacting sub problems: mode assignment and activity scheduling. These problems cannot be solved in isolation because of the interaction that exists between them. Many evolutionary algorithms have been applied to this problem most commonly the Genetic Algorithm (GA). It has been common practice to improve the performance of the GA with some local search techniques. The Bi-population Genetic Algorithm (BPGA) is one of the most competitive GAs for solving the MRCPSP. In this paper, we improve the BPGA by hybridising it with an Estimation of Distribution Algorithm that focuses on improving how modes are generated. We also suggest improvement to the existing experimental methodology.