The impact of approximate evaluation on the performance of search algorithms for warehouse scheduling

✍ Scribed by Watson, J. P. (author);Rana, S. (author);Whitley, L. D. (author);Howe, A. E. (author)

• Publisher: Springer Netherlands
• Year: 1999
• Tongue: English
• Weight: 254 KB
• Volume: 2
• Category: Article
• ISSN: 1094-6136
• DOI: 10.1002/(sici)1099-1425(199903/04)2:2<79::aid-jos19>3.0.co;2-h

✦ Synopsis

The Coors warehouse scheduling problem involves finding a permutation of customer orders that minimizes the average time that customers' orders spend at the loading docks while at the same time minimizing the running average inventory, Search-based solutions require fast objective functions. Thus, a fast lowresolution simulation is used as an objective function. A slower high-resolution simulation is used to validate solutions. We compare the performance of a constructive scheduling algorithm to a genetic algorithm and local search approach. The constructive algorithm is based on a heuristic built specifically for this application. We also tested a hybrid of the genetic algorithm and local search approaches by initializing the search using the domain-specific heuristic. This hybrid genetic algorithm was able to find the best solutions when evaluated by the high-resolution simulation. Finally, we consider the effect of using the high-resolution simulation to filter a set of solutions found by the different approaches.