An ant colony optimization based hyper-heuristic for the mixed model assembly line balancing problem with setups

The assembly line balancing problems get turn into a hierarchical nature, which refers that the assignment problem must be solved simultaneously with a sequencing problem, in the presence of setup times that depend on the task execution sequences. This paper tries to design a hyper-heuristic, which tries to explore a search space of heuristics rather than a search space of solutions, to solve the mixed model assembly line balancing problem with setups. In line with this purpose, the ant colony optimization algorithm is employed to explore the search space composed of several assembly line balancing heuristics. Namely, this paper proposes an effective ant colony optimization based hyper-heuristic to tackle the assembly line balancing problems with sequence-dependent setup times. The performance evaluation tests of the designed hyper-heuristic are done on the benchmark instances taken from the related literature. The obtained results indicate the effectiveness of the designed algorithm.