Constructive-destructive neighbor search drives artificial bee colony algorithm for variable speed green hybrid flowshop scheduling problem

The hybrid flowshop scheduling problem (HFSP), a typical NP-hard problem, has gained significant interest from researchers focusing on the development of solution methods. We focus on a variable speed hybrid flowshop scheduling problem. We assume that machines operate at variable speed when processing workpieces, making the problem more reflective of real-world scenarios. Aiming at this problem, a speed optimization strategy for encoding and decoding is proposed. Meanwhile, we design a constructive-destructive search driven artificial bee colony algorithm to solve the variable-speed green hybrid flow shop scheduling problem to minimize the makespan and total energy consumption. A constructive-destructive neighbor search method is designed to update population search in the employed bee phase. The search process is redesigned with three operators named the technique of order preferences for similarity of ideal solutions, binary tournament selection, and global update strategies in the onlooker bee phase. In the scout bee phase, individual evaluation and replacement strategies are designed. Extensive experimental evaluations testify that the CDSABC outperforms other algorithms regarding the best, worst, average, and standard deviation of the IGD index in 80% of the test cases.