Improved discrete cuckoo optimization algorithm for the three-stage assembly flowshop scheduling problem

The three-stage assembly flow shop scheduling problem, where the first stage has parallel machines and the second and the third stages have a single machine, is addressed in this study. Each product has made of several components that after processing at the first stage are collected and transferred to the third stage to assemble them as the product. The goal is to find products’ sequence to minimize completion time of the last product, makespan. Since the problem is NP-hard, an improved version of Cuckoo Optimization Algorithm (COA), a bio-inspired meta-heuristic, is proposed which incorporates new adjustments such as clustering, egg laying and immigration of the cuckoos based on a discrete representation scheme. These novel features result in an Improved Discrete version of COA, called IDCOA, which works efficiently. Also, for the addressed problem, a lower bound and some dispatching rules are proposed. The performance of the employed algorithms through randomly generated instances is evaluated which endorses the capability of the proposed IDCOA algorithm.