A feedback-based artificial bee colony algorithm for energy-efficient flexible flow shop scheduling problem with batch processing machines

Abstract

Energy-efficient flexible flow shop scheduling problem (EFFSP) and parallel batch processing machines (BPM) scheduling problem have been extensively studied; however, as the integration of EFFSP and parallel BPM scheduling problem, EFFSP with BPM is seldom investigated even though it often exists in many energy-intensive manufacturing processes such as casting and steelmaking. In this study, EFFSP with BPM at a middle stage in hot & cold casting process is considered, and a feedback-based artificial bee colony (FABC) algorithm is proposed to simultaneously minimize makespan, total tardiness, and total energy consumption. A new cooperation between two employed bee swarms and three search cases are implemented, which are employed bee phase and onlooker bee phase or employed bee phase and cooperation or employed bee phase. Feedback mechanism is established by evolution quality of employed bee swarms and adaptive threshold and used to dynamically determine which search case is executed on each generation. New scout phase and recombination operator are also applied. Extensive experiments are conducted and the computational results demonstrated that new strategies such as cooperation are effective and FABC has promising advantages in the considered EFFSP.