A differential evolution-based memetic algorithm for project scheduling problems. (2015) - Shen, Xiaoning; Zhang, Min
A differential evolution (DE)-based memetic algorithm (MA) for solving the project scheduling problem (PSP) is proposed. In order to balance the abilities of exploration and exploitation, the proposed DE-based MA (DEMA) combines the DE-based global search with a problem-specific local search operator. In particular, DEMA applies evolutionary search schemes of DE to explore the large search space, where an improved mutation strategy that both uses vector differences for perturbation and learns from the current best solution is adopted. Besides, to make DE suitable for solving PSP which is a combinational optimisation problem, a slackness method is designed to convert between discrete dedications in PSP and continuous vectors in DE. On the other hand, a local search with two neighbourhood structures is utilised to exploit the local information around current solutions so that the solution quality can be further improved. Simulation results on real-world PSP instances validate the superiority of DEMA over state-of-the-art search-based approaches and the effectiveness of new mechanisms designed in DEMA.