| dc.contributor.author | Baldomero Naranjo, Marta | |
| dc.contributor.author | Martínez Merino, Luisa Isabel | |
| dc.contributor.author | Rodríguez Chía, Antonio Manuel | |
| dc.contributor.other | Estadística e Investigación Operativa | es_ES |
| dc.date.accessioned | 2024-03-11T08:27:29Z | |
| dc.date.available | 2024-03-11T08:27:29Z | |
| dc.date.issued | 2024 | |
| dc.identifier.issn | 0360-8352 | |
| dc.identifier.uri | http://hdl.handle.net/10498/31345 | |
| dc.description.abstract | This paper introduces a new hierarchical facility location model with three levels: first-level facilities which manufacture different products, second-level facilities which act as warehouses and a third-level consisting of the clients who demand the products that have been manufactured in the first level and stored in the second level. In this model, called multi-product maximal covering second-level facility location problem (SL-MCFLP), the aim is to decide the location of the second-level facilities and the products to be stored in each of them maximizing the overall clients’ satisfaction with respect their coverage. To deal with this model, we introduce a Mixed Integer Linear Program (MILP) which is reinforced by some families of valid inequalities. Since some of these families have an exponential number of constraints, separation algorithms are proposed. In addition, three variants of a matheuristic procedure are developed. Computational studies are included, showing the potentials and limits of the formulation and the effectiveness of the heuristic. | es_ES |
| dc.format | application/pdf | es_ES |
| dc.language.iso | eng | es_ES |
| dc.publisher | Elsevier | es_ES |
| dc.source | Computers & Industrial Engineering 189 (2024) 109961 | es_ES |
| dc.subject | Hierarchical location | es_ES |
| dc.subject | Covering | es_ES |
| dc.subject | Integer programming | es_ES |
| dc.subject | Matheuristic | es_ES |
| dc.title | Multi-product maximal covering second-level facility location problem | es_ES |
| dc.type | journal article | es_ES |
| dc.rights.accessRights | open access | es_ES |
| dc.identifier.doi | 10.1016/j.cie.2024.109961 | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2020-2023/TED2021-130875B-I00/ES/Optimización de recursos y de cadenas de producción. | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/RED2022-134149-T/ES/RED TEMATICA: CIENCIA DE LA LOCALIZACION Y PROBLEMAS AFINES/ | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114594GB-C22/ES/OPTIMIZATION ON DATA SCIENCE AND NETWORK DESIGN PROBLEMS: DATA SCIENCE MEETS OPTIMIZATION AND NETWORK MODELS/ | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/Junta de Andalucía//AT 21_00032/ | es_ES |
| dc.type.hasVersion | VoR | es_ES |