Abstract
In this paper, a new multiple population based meta-heuristic to solve combinatorial optimization problems is introduced. This meta-heuristic is called Golden Ball (GB), and it is based on soccer concepts. To prove the quality of our technique, we compare its results with the results obtained by two different Genetic Algorithms (GA), and two Distributed Genetic Algorithms (DGA) applied to two well-known routing problems, the Traveling Salesman Problem (TSP) and the Capacitated Vehicle Routing Problem (CVRP). These outcomes demonstrate that our new meta-heuristic performs better than the other techniques in comparison. We explain the reasons of this improvement.
| Original language | English |
|---|---|
| Pages (from-to) | 145-166 |
| Number of pages | 22 |
| Journal | Applied Intelligence |
| Volume | 41 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Jul 2014 |
| Externally published | Yes |
Keywords
- Combinatorial optimization
- Distributed genetic algorithm
- Golden ball
- Intelligent transportation systems
- Meta-heuristics
- Routing problems
