An improved artificial bee colony algorithm for the blocking flowshop scheduling problem

This paper presents an improved artificial bee colony (IABC) algorithm for solving the blocking flowshop problem with the objective of minimizing makespan. The proposed IABC algorithm utilizes discrete job permutations to represent solutions and applies insert and swap operators to generate new solutions for the employed and onlooker bees. The differential evolution algorithm is employed to obtain solutions for the scout bees. An initialization scheme based on the problem-specific heuristics is presented to generate an initial population with a certain level of quality and diversity. A local search based on the insert neighborhood is embedded to improve the algorithm's local exploitation ability. The IABC is compared with the existing hybrid discrete differential evolution and discrete artificial bee colony algorithms based on the well-known flowshop benchmark of Taillard. The computational results and comparison demonstrate the superiority of the proposed IABC algorithm for the blocking flowshop scheduling problems with makespan criterion.