Hybrid Gray Wolf Algorithm for No Wait Flow Shop Scheduling Problems

Abstract

No-wait flowshop scheduling is an optimization problem that finds wide application in the chemical industry, pharmaceutical industry, steel melting and casting industries. Flight scheduling, operating room scheduling, train line scheduling are a few examples of no-wait scheduling problems. Such problems are called NP-Hard optimization problems in the literature. Researchers have developed various methods to solve such problems. In this study, a gray wolf optimization algorithm is presented to minimize the maximum completion time for nowait flow shop scheduling problems. The local search algorithm has been adapted and hybridized in order to prevent the algorithm from getting stuck in local optima and to enable it to search in the global area. In addition, in order to increase the solution variety and quality of the proposed algorithm, the majority of the initial populations were created with sorting rules instead of random generation. It has been observed that the algorithm tested with the problem sets in the literature gives effective results compared to other methods compared.