This paper addresses a new steelmaking-continuous casting (SCC) scheduling problem from iron and steel production processing. We model the problem as a combination of two coupled sub-problems. One sub-problem is a charge scheduling problem in a hybrid flowshop, and the other is a cast scheduling problem in parallel machines. To solve this SCC problem, we present a novel cooperative co-evolutionary artificial bee colony (CCABC) algorithm that has two sub-swarms, with each addressing a sub-problem. Problem-specific knowledge is used to construct an initial population, and an exploration strategy is introduced to guide the CCABC to promising regions during the search. To adapt the search operators in the classical artificial bee colony (ABC) to the cooperative co-evolution paradigm, an enhanced strategy for onlookers and a self-adaptive neighbourhood operator have been suggested. Extensive experiments based on both synthetic and real-world instances from an SCC process show the effectiveness of the proposed CCABC in solving the SCC scheduling problem. 
An effective co-evolutionary artificial bee colony algorithm for steelmaking-continuous casting scheduling