Comparing cuckoo search, bee colony, firefly optimization, and electromagnetism-like algorithms for solving the set covering problem
Autor
Soto R.
Crawford B.
Galleguillos C.
Barraza J.
Lizama S.
Muñoz A.
Vilches J.
Misra S.
Paredes F.
Resumen
The set covering problem is a classical model in the subject of combinatorial optimization for service allocation, that consists in finding a set of solutions for covering a range of needs at the lowest possible cost. In this paper, we report various approximate methods to solve this problem, such as Cuckoo Search, Bee Colony, Firefly Optimization, and Electromagnetism-Like Algorithms. We illustrate experimental results of these metaheuristics for solving a set of 65 non-unicost set covering problems from the Beasley’s OR-Library. © Springer International Publishing Switzerland 2015.
Colecciones
Ítems relacionados
Mostrando ítems relacionados por Título, autor o materia.
-
Conference Paper
Modified binary firefly algorithms with different transfer functions for solving set covering problems (2020)
Crawford B.; Soto R.; Riquelme-Leiva M.; Peña C.; Torres-Rojas C.; Johnson F.; Paredes F. (Springer Verlag, 2015) -
Conference Paper
A XOR-based ABC algorithm for solving set covering problems (2020)
Soto R.; Crawford B.; Lizama S.; Johnson F.; Paredes F. (Springer Verlag, 2016) -
Conference Paper
A teaching-learning-based optimization algorithm for solving set covering problems (2020)
Crawford B.; Soto R.; Aballay F.; Misra S.; Johnson F.; Paredes F. (Springer Verlag, 2015)