HYBRID GENETIC ALGORITHM FOR ASSEMBLY FLOW-SHOP SCHEDULING PROBLEM WITH SEQUENCE-DEPENDENT SETUP AND TRANSPORTATION TIMES

Flow shop assembly production system is a system that combines different manufactur ing operat ions independently and simultaneously and then the manufacturing parts are collected and transmitted to assembly line. In this problem, a set of parts is produced by independent production line and finally converted to the product by assembly stage. This type of assembly manufacturing system can be a solution to respond to market pressure to manufacture different products. Global competition and the need to control production costs, lead companies to manufacture products, so that by combining parts and sub-assemblies they will be able to manufacture more various products. This is one of the greatest benefits of these structures. In scheduling perspective, this type of manufacturing systems can be modeled such as two-stage assembly flow shop. Considering the time of collection and transportation of parts from the production stage to the assembling stage, we will face a more realistic model of the two-stage assembly flow-shop problem. It is possible to put this assumption as a discrete phase between the production and assembly stages. Thus the model can be closer to reality and we will have a three-stage model. Three-stage flow shop assembly problem is an extended mode of the two-stage flow shop assembly problem. In the two-stage flow shop assembly problem, it is assumed that each job is made of pieces, which are produced on parallel machines. The required time for collecting and transporting m completed parts from the first stage to the second is very short. This assumption is particularly inappropriate especially when we use the twostage assembly flow shop problem for the simulation of manufacturing systems with several industrial units (Factory) and a unit assembly. In these systems the main m m

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