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Combining Simulation with Heuristics to solve Stochastic Routing and Scheduling Problems
| Content Provider | Semantic Scholar |
|---|---|
| Author | Dangelmaier, Wilhelm Laroque, Christoph Klaas, Alexander Paderborn, Hni-Verlagsschriftenreihe Juan, Angel A. Rabe, M. Dortmund, Tu |
| Copyright Year | 2013 |
| Abstract | Many real-world problems in the production and logistics business are NPhard even in their deterministic representation, and actually also show stochastic behaviour, where even the mathematical description of the – frequently empirical – distributions is difficult or even impossible. Therefore, an approach is acquired that enables the search for valid and reasonably good solutions under representation of the stochastic system behaviour. A suitable approach is to combine heuristic optimization with simulation techniques. This paper discusses how Monte-Carlo simulation can be combined with heuristics and meta-heuristics in order to efficiently solve such stochastic combinatorial optimization problems. The application is illustrated with examples in two different fields, including logistics and transportation – e.g. vehicle routing problems and inventory problems – as well as manufacturing and production – e.g. scheduling problems. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.asim-fachtagung-spl.de/asim2013/papers/Proof_176_Juan.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
