Abstract
Large-scale unconditional and conditional vertex p-centre problems are solved using two meta-heuristics. One is based on a three-stage approach whereas the other relies on a guided multi-start principle. Both methods incorporate Variable Neighbourhood Search, exact method, and aggregation techniques. The methods are assessed on the TSP dataset which consist of up to 71,009 demand points with p varying from 5 to 100. To the best of our knowledge, these are the largest instances solved for unconditional and conditional vertex p-centre problems. The two proposed meta-heuristics yield competitive results for both classes of problems.
| Original language | English |
|---|---|
| Pages (from-to) | 507-537 |
| Number of pages | 31 |
| Journal | Journal of Heuristics |
| Volume | 22 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Aug 2016 |
| Externally published | Yes |
Free Keywords
- Aggregation
- Exact method
- Large unconditional and conditional vertex p-centre
- Variable neighbourhood search
ASJC Scopus subject areas
- Software
- Information Systems
- Computer Networks and Communications
- Control and Optimization
- Management Science and Operations Research
- Artificial Intelligence