Job scheduli̇ng wi̇th the help of dominance properties and genetic algorithm on hybrid flow shop problem with unrelated parallel machine

Todays' developed technology makes not only products but also manufacturing systems complex. Products are accessed easier with the industrial revolution. Product accessibility increases the customer demand. Consequently, to satisfy increased customer demands companies expand their manufacturing capacities. After a literature review, we determined that there is hardly any study on "unrelated parallel machine and set up time constrained Hybrid Flow Shop" problems. Specifically, the techniques, i.e, dominance properties, that help heuristics methods are not used. In almost all studies, either heuristics or meta-heuristics methods are applied. The problem complexity plays an important role in selecting the solution methodologies. In this dissertation, genetic algorithm, which is an evolutionary algorithm, with dominance property is used to solve the proposed problem.