A data-driven ensemble algorithm of black widow optimizer and simulated annealing algorithms for multi-objective buffer allocation in production lines

The multi-objective buffer allocation problem of production lines is a non-deterministic-polynomial-hard problem. Many metaheuristic algorithms have been proposed to solve this problem. However, further investigation of new algorithms is still required because metaheuristic algorithms highly depend on the problem types. Furthermore, the balance between the solution quality and computational efficiency requires further improvement. Therefore, a data-driven algorithm consisting of the black widow optimizer and simulated annealing algorithm is proposed to maximize throughput and minimize energy consumption in production lines. Numerical examples demonstrate that the proposed algorithm achieves better solution quality than other state-of-the-art algorithms without losing computational efficiency. This study contributes to multi-objective optimization of resource scheduling in production lines.