Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/312828 
Year of Publication: 
2023
Citation: 
[Journal:] Journal of Heuristics [ISSN:] 1572-9397 [Volume:] 29 [Issue:] 4 [Publisher:] Springer US [Place:] New York, NY [Year:] 2023 [Pages:] 435-460
Publisher: 
Springer US, New York, NY
Abstract: 
In the family traveling salesman problem (FTSP), there is a set of cities which are divided into a number of clusters called families. The salesman has to find a shortest possible tour visiting a specific number of cities from each of the families without any restriction of visiting one family before starting the visit of another one. In this work, the general concept of the Partial OPtimization Metaheuristic Under Special Intensification Conditions is linked with the exact optimization by a classical solver using a mathematical programming formulation for the FTSP to develop a matheuristic. Moreover, a genetic and a simulated annealing algorithm are used as metaheuristics embedded in the approach. The method is examined on a set of benchmark instances and its performance is favorably compared with a state-of-the-art approach from literature. Moreover, a careful analysis of the specific components of the approach is undertaken to provide insights into the impact of their interplay.
Subjects: 
Matheuristic
Partial optimization metaheuristic under special intensification conditions
Genetic algorithm
Family traveling salesman problem
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.