Study on No-Wait Flexible Flow Shop Scheduling with Multi-objective

摘要

A multi-objective flexible flow shop scheduling model is constructed inclusive of production period, total expense, and mean flow time, which is based on the characteristics of dual-resource constrained no-wait flow shop scheduling problem with unrelated parallel machines. A genetic algorithm based on Pareto is proposed to solve the multi-objective scheduling problem. Then, consider the machine and worker constraints, and unrelated parallel machines and the successive processing, the production period is given through pushing reversely from the operation. The starting time of some jobs will be delayed and the spare time of machines will be increased in order to ensure the consecutive operations of the same job. Considering three objectives, an optimal set is given, and compared to other algorithms, simulation results show that the method is effective and feasible. At last, a comparative analysis of the same case is made from no-wait flow shop scheduling and flow shop scheduling with non-consecutive operation.