Article ID: | iaor20062024 |
Country: | United Kingdom |
Volume: | 55 |
Issue: | 12 |
Start Page Number: | 1342 |
End Page Number: | 1351 |
Publication Date: | Dec 2004 |
Journal: | Journal of the Operational Research Society |
Authors: | Li Y., Lim A., Rodrigues B. |
Keywords: | genetic algorithms, Crossdocking |
In this paper, we study a problem central to crossdocking that aims to eliminate or minimize storage and order picking activity using JIT scheduling. The problem is modelled naturally as a machine scheduling problem. As the problem is NP-hard, and for real-time applications, we designed and implemented two heuristics. The first uses Squeaky Wheel Optimization embedded in a Genetic Algorithm and the second uses Linear Programming within a Genetic Algorithm. Both heuristics offer good solutions in experiments where comparisons are made with the CPLEX solver.