A discrete whale optimization algorithm for the no-wait flow shop scheduling problem

A discrete whale optimization algorithm (DWOA) is presented to solve the no-wait flow shop scheduling problem (NWFSSP) with objective makespan. An effective combination of nearest neighbor (NN) and standard deviation heuristics (SDH) used acquire initial solutions population. After that, three crossover operators, two-point (TPX), multiple-point (MPX) job-based (JBX) are designed mimics humpback whales hunting process. Moreover, dynamic transform mechanism search process better balance exploration exploitation ability DWOA. In order further improve effect DWOA, parallel neighborhood (PNS) serial (SNS) selected execute local promoting global scheme, respectively. Finally, test performance extensive experiments conducted on benchmarks by Reeves Taillard, which contain parameters tuning, effectiveness improvement strategies in DWOA comparison several existing algorithms. From experimental results, it validated that improved mechanisms can find makespan values compared other algorithms for solving NWFSSP.