Solving Distributed Scheduling problem with Alternative Routings by Genetic Algorithms

摘要

Multi-factory production network is prevalent in recent years. With the factories located geographically in different areas, company can benefit various advantages, such as closer to their customers, and response faster to the market changes. Products (jobs) in the network can usually be produced in more than one suitable factory. However, each factory has its product efficiency, capacity, and utilization level. This makes distributed scheduling more complicate than classical production scheduling problem. It has to simultaneously determine how to allocate jobs into suitable factory, and the corresponding production scheduling as well. The problem is even more complicated when alternative production routing is allowed in factories. This paper proposed genetic algorithm approach to deal with distributed scheduling problems, especially in alternative production routings environment. A new idea named dominant genes and a crossover mechanism is designed to enhance the performance of genetic search. The proposed algorithm has been run on several distributed scheduling problems. The results have been compared to those obtained by other approaches and simple genetic algorithms. It indicates that the proposed approach performs better.