An ABC Algorithm Minimizing Regular Objectives for Blocking Permutation Flow Shop Scheduling Problem

In this paper, we expose a new meta-heuristic based on the artificial behavior of bee colony (ABC) for solving the blocking permutation flow shop scheduling problem (BFSP) subject to regular objectives. On three main steps, the proposed algorithm iteratively solved the BFSP under three fixed measure (makespan, total flowtime, or total tardiness criterion). Discrete job permutations and operators are used to represent and generate new solutions for the employed, the onlookers, and scout bees, respectively. The performance of this algorithm is tested on the well-known benchmark sets of Taillard, and Ronconi and Henriques. The computational results assert the effectiveness of this heuristic in comparison with some recently proposed state-of-the-art algorithms. So, new best known solutions for the benchmark sets are found for the considered problem.