A hybrid meta-heuristic for balancing and scheduling assembly lines with sequence-independent setup times by considering deterioration tasks and learning effect

This paper addresses the Simple Assembly Line Balancing Problem of type II (SALBP-II), with simultaneous effects of deterioration and learning in which there are sequence-independent setup times relating to each task. In many real industrial environments, although the actual task processing times are defined as a function of their starting times due to deterioration effects, workstations improve continuously as a result of repeating the same activities by worker(s) or machine(s). In this paper, a mathematical model is developed for this novel problem, attempting to minimize the cycle time for a given number of workstations. In addition to the balancing of the assembly line, the developed model presents the execution scheduling of tasks assigned to each workstation. Moreover, a hybrid meta-heuristic method is proposed to solve such an NP-hard problem. This robust and simply structured solution approach uses the tabu search within the Variable Neighbourhood Search (VNS/TS). The computational experiments and comparison with a Differential Evolution Algorithm (DEA) reflect the high efficiency of our proposed algorithm for a number of well-known instances.