Initialization and Local Search Methods Applied to the Set Covering Problem: A Systematic Mapping
Revista Facultad De Ingenieria, Universidad Pedagogica Y Tecnologica De Colombia
; 32(63), 2023.
Artículo
en Inglés
| Web of Science | ID: covidwho-2310498
ABSTRACT
The set covering problem (SCP) is a classical combination optimization problem part of Karp's 21 NP-complete problems. Many real-world applications can be modeled as set covering problems (SCPs), such as locating emergency services, military planning, and decision-making in a COVID-19 pandemic context. Among the approaches that this type of problem has solved are heuristic (H) and metaheuristic (MH) algorithms, which integrate iterative methods and procedures to explore and exploit the search space intelligently. In the present research, we carry out a systematic mapping of the literature focused on the initialization and local search methods used in these algorithms that have been applied to the SCP in order to identify them and that they can be applied in other algorithms. This mapping was carried out in three main stages research planning, implementation, and documentation of results. The results indicate that the most used initialization method is random with heuristic search, and the inclusion of local search methods in MH algorithms improves the results obtained in comparison to those without local search. Moreover, initialization and local search methods can be used to modify other algorithms and evaluate the impact they generate on the results obtained.
Texto completo:
Disponible
Colección:
Bases de datos de organismos internacionales
Base de datos:
Web of Science
Tipo de estudio:
Revisión sistemática/Meta análisis
Idioma:
Inglés
Revista:
Revista Facultad De Ingenieria, Universidad Pedagogica Y Tecnologica De Colombia
Año:
2023
Tipo del documento:
Artículo
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