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.