| Full text | |
| Author(s): |
Maximo, Vinicius R.
;
Cordeau, Jean-Francois
;
Nascimento, Maria C. V.
Total Authors: 3
|
| Document type: | Journal article |
| Source: | International Transactions in Operational Research; v. 32, n. 1, p. 18-pg., 2023-10-14. |
| Abstract | |
Adaptive iterated local search (AILS) is a recently proposed metaheuristic paradigm that focuses on adapting the diversity control of iterated local search by online learning mechanisms. It has been successfully applied to the capacitated vehicle routing problem (CVRP) and the heterogeneous vehicle routing problem. Hybridizing it with path relinking (PR) has further improved the intensification of the method for the CVRP, providing outstanding results. However, the potential of this metaheuristic has not yet been investigated on other combinatorial optimization problems, such as location problems. In this paper, we develop a version of AILS for the maximal covering location problem (MCLP). This problem consists of locating a number of facilities to maximize the covered customer demand, where a given facility location can meet the demand of customers located within a coverage radius. Experiments on large-scale instances of the MCLP indicate that AILS hybridized with PR, called AILS-PR, outperforms the state-of-the-art metaheuristic. (AU) | |
| FAPESP's process: | 10/50646-6 - High performance computing applied in interdisciplinary problems |
| Grantee: | Vitor Rafael Coluci |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 16/01860-1 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings |
| Grantee: | Reinaldo Morabito Neto |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 22/05803-3 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings |
| Grantee: | Reinaldo Morabito Neto |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 19/22067-6 - Learning strategies for heuristic search in combinatorial optimization problems |
| Grantee: | Mariá Cristina Vasconcelos Nascimento Rosset |
| Support Opportunities: | Scholarships abroad - Research |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |