Abstract
This study is a case for Semiconductor Assembly Factory and consider hybrid flow shop problem for lot streaming and dispatching rule. Consider orders with a known arrival time, unrelated parallel machines for machine group, identical parallel machines within machine group, machine eligibility about different product, the processing time with randomness, specific production about lot streaming and batch processor to a scheduling problem. The objective function is to minimize mean flow time of the orders in the study. The problem is to determine the dispatching rule of each stage, the lot size of each job after the first stage, and the assignment machine group of each job to process in each stage. Because of specific production environment, the assignment problem is completive. To address this problem, we develop the simulation optimization approach. To overcome too many alternatives to exhaust, genetic algorithm is used when the search space is large. Elite Group Optimal computing budget allocation(EGOCBA) is used to reduce simulation budget and time while processing time of machines has randomness. The conclusion of this study presents the superior mean flow time in the problem of dispatching rule with lot streaming.