1179. Metaheuristics for the Induced p-Median problem with Upgrades
Invited abstract in session TB-15: Heuristic Search 2, stream Combinatorial Optimization.
Tuesday, 10:30-12:00Room: Esther Simpson 1.08
Authors (first author is the speaker)
| 1. | Sergio Salazar
|
| Dpto. Statistics and Computer Science, Rey Juan Carlos University | |
| 2. | J. Manuel Colmenar
|
| Universidad Rey Juan Carlos |
Abstract
Facility location problems (FLPs) are a family of optimisation problems with significant social impact. This class of problems has been the subject of study since the 1960s, with classical approaches including the Weber Problem and the p-median Problem. At the present time, more complex variations of these problems are being investigated. Notably, the Induced p-Median Problem with Upgrading (IpMU) represents a variation of the classical p-Median problem, where the concepts of transport cost and distance are separated as distinct metrics in the input graph of the problem. Furthermore, a set of decision variables is incorporated to relax the costs of the graph, allowing the edges between nodes to be reduced, thus enhancing the associated routes between the designated medians and the customers. In this study, a metaheuristic algorithm is proposed based on the Greedy Random Adaptive Search Procedure (GRASP), wherein a two-phase resolution scheme is established, studying the median problem and the improvement problem independently. In this approach, a large set of state-of-the-art instances has been analysed to ensure a fair comparison with previous proposals. The results obtained are promising when compared to the state of the art, which is based entirely on mathematical models. Execution time has been improved with the same or better quality results in all the studied instances.
Keywords
- Metaheuristics
- Combinatorial Optimization
- Location
Status: accepted
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