Abstract
This paper formulates and compares four new approaches to optimally locate the input and output station for each department within a facility design such that material handling costs are minimized. This problem is an NP-hard combinatorial problem with many real-life applications of considerable economic consequence. A genetic algorithm (GA) is shown to be an effective and efficient optimization method when compared to integer programming, simulated annealing, and three versions of a greedy constructive heuristic on a suite of test problems of varying size. Seeding versus random initialization of GA populations are compared.
| Original language | English |
|---|---|
| Pages (from-to) | 192-203 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Evolutionary Computation |
| Volume | 5 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jun 2001 |
Keywords
- Genetic alogorithms
- Materials handling
- Optimization methods
Fingerprint Dive into the research topics of 'Locating input and output points in facilities design - A comparison of constructive, evolutionary, and exact methods'. Together they form a unique fingerprint.
Cite this
Arapoglu, R. A., Norman, B. A., & Smith, A. E. (2001). Locating input and output points in facilities design - A comparison of constructive, evolutionary, and exact methods. IEEE Transactions on Evolutionary Computation, 5(3), 192-203. https://doi.org/10.1109/4235.930310