Genetic Algorithms for Scheduling

Abstract

This paper provides a survey of the application of genetic algorithms (GAs) to scheduling. Although it focuses on manufacturing scheduling, particularly job-shop problems, it does outline work in other areas such as transport scheduling and network routing. GA research in closely related problems, such as bin packing and the TSP, are also covered. Finally, it is shown how distributed parallel GAs may allow practically beneficial recharacterisations of highly complex general scheduling problems. 1 Introduction Practical scheduling problems are numerous and varied. However, many of them share two important characteristics --- they are very difficult, and good quality solutions bring highly tangible benefits. In general, scheduling problems are NP-hard [37], consequently there are no known algorithms guaranteed to give an optimal solution and run in polynomial time. This has lead to a long line of techniques emanating from the fields of AI and OR that provide approximate solutions to fai..