On-line simulation tools are often coupled with optimization tools for on-line control and scheduling solutions: artificial intelligence, genetic algorithms, simulated annealing, heuristics, dynamic programming, linear programming, to name a few. Yet, most success stories of on-line control depend on how the scheduling tool was deployed more so than the specifics of the algorithms or optimization tools that are used. This paper addresses the critical factors that make on-line, simulation-based scheduling applications successful and identifies promising future prospects.
| Number of Pages : | 5 |
| Published : | 11/01/1998 |
