Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1342-1351 |
| Journal | Journal of the Operational Research Society |
| Volume | 55 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - Dec 2004 |
| Externally published | Yes |
Research Keywords
- Crossdock
- Heuristics
- Just-in-time scheduling
- Machine scheduling
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