Hybrid Differential Evolution and Greedy Algorithm (DEGR) for solving Multi-Skill Resource-Constrained Project Scheduling Problem

Abstract

Paper presents a hybrid Differential Evolution and Greedy Algorithm (DEGR) applied to solve Multi-Skill Resource-Constrained Project Scheduling Problem. The specialized indirect representation and transformation of solution space from discrete (typical for this problem), to continuous (typical for DE-approaches) are proposed and examined. Furthermore, Taguchi Design of Experiments method has been used to adjust parameters for investigated method to reduce the procedure of experiments. Finally, various initialisation, clone elimination, mutation and crossover operators have been applied there. The results have been compared with the results from other reference methods (HantCO, GRASP and multiStart Greedy) using the benchmark iMOPSE dataset. This comparison shows that DEGR effort is very robust and effective. For 28 instances of iMOPSE dataset DEGR has achieved the best-known solutions.