An improved genetic algorithm with local search for order acceptance and scheduling problems

The research on order acceptance and scheduling problems, which combine the selection with scheduling, is an important subject in production systems and has attracted attentions from both academia and practitioners. In this paper, we propose an improved genetic algorithm (GA) with local search, named IGAL, for the order acceptance and scheduling problems with tardiness penalties and sequence-dependent setup times in single machine environment. In order to improve the performance of the classical GA for the focused problems, two effective local search strategies are adopted in IGAL. The efficacy of IGAL was evaluated on 1500 instances with up to 100 orders. Experimental results showed that the proposed IGAL is quite competitive when compared with five other methods.