A new bi-objective evolutionary algorithm using clustering heuristics to solve the Multi-mode Resource-Constrained Project Scheduling Problem
نویسنده
چکیده
In this paper, the non preemptive multi-mode resourceconstrained project scheduling is considered. We use a biobjective approach to solve the mono-objective problem of makespan minimization. Our main focus is to propose a high-performance algorithm that solves the problem at hand. A new evolutionary algorithm is developed. The encoding procedure is based on feasible activity list and a mode assignment. We define two new fitness functions dealing with clustering tools, namely k-means and hierarchical clustering algorithms. Results of the implementation are emphasized to decide on the best algorithm configuration. The latter is used to compare our algorithm performance to other recent heuristics and metaheuristics. Standard instances sets included in PSPLIB are tested. The results testify the good performance of our new hybrid evolutionary algorithm.
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