An Improved Artificial Bee Colony algorithm for real-world hybrid flowshop rescheduling in Steelmaking-refining-Continuous Casting process

Realistic production systems usually encounter various of unexpected disruptions, which may invalidate the original schedules, and thus rescheduling becomes essential. This paper studies a real-world hybrid flowshop rescheduling problem in Steelmaking-refining-Continuous Casting (SCC) process, where machine breakdown is considered as the disruption, and controllable processing times in the last stage of SCC process is considered. An Improved Artificial Bee Colony (IABC) algorithm is developed to solve the problem. In the IABC, novel encoding and decoding strategies are devised to represent the solutions effectively, where a charge left-shifting strategy is designed to decrease cast break. A population initialization heuristic is devised to generate solutions with a high level of quality and diversity. Meanwhile, a variable neighboring operator, which can balance the exploration and exploitation abilities, is proposed to generate new solutions with high quality for the employed bee and onlooker bee phases. Moreover, a worst solution replacement strategy is developed to further enhance the exploitation ability. To demonstrate the performance of the IABC, comprehensive computational comparisons against several state-of-the-art algorithms and statistical analysis are conducted, which discloses the strength and availability of the IABC. Moreover, key features of the IABC are analyzed, confirming their critical roles to the success of the IABC.