Abstract
The Hub Location Problem (HLP) has been an attractive area of research
for more than four decades. A recently proposed problem in the area of hub location is the hierarchical Single-Allocation Hub Median Problem (SA-H-MP), which is associated with finding the location of a number of hubs and central hubs, so that the total routing cost is minimized. Owing to the problem's complexity and intractability, this paper puts forward two metaheuristics, Simulated Annealing (SA) and Iterated Local Search (ILS), and compares their performances. Results show that while both algorithms are able to reach optimal solutions on the standard CAB data-set, their run-times are negligible and considerably lower compared to the run-times of exact methods.
for more than four decades. A recently proposed problem in the area of hub location is the hierarchical Single-Allocation Hub Median Problem (SA-H-MP), which is associated with finding the location of a number of hubs and central hubs, so that the total routing cost is minimized. Owing to the problem's complexity and intractability, this paper puts forward two metaheuristics, Simulated Annealing (SA) and Iterated Local Search (ILS), and compares their performances. Results show that while both algorithms are able to reach optimal solutions on the standard CAB data-set, their run-times are negligible and considerably lower compared to the run-times of exact methods.
Original language | English |
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Pages (from-to) | 1203 |
Number of pages | 1217 |
Journal | Scientia Iranica |
Volume | 22 |
Issue number | 3 |
Publication status | Published - 2015 |
Keywords
- Location
- Simulated annealing
- Iterated local search
- Heuristics
- Metaheuristics