Fisherman Search Procedure
| Autor: | Oscar José Alejo Machado, Eduardo R. Concepción Morales, Juan Francisco Huete Guadix, Juan Manuel Fernandez Luna |
|---|---|
| Rok vydání: | 2012 |
| Předmět: | |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783642346538 IBERAMIA |
| Popis: | Optimization is used in diverse areas of science, technology and business. Metaheuristics are one of the common approaches for solving optimization problems. In this paper we propose a novel and functional metaheuristic, Fisherman Search Procedure (FSP), to solve combinatorial optimization problems, which explores new solutions using a combination of guided and local search. We evaluate the performance of FSP on a set of benchmark functions commonly used for testing global optimization methods. We compare FSP with other heuristic methods referenced in literature, namely Differential Evolution (DE), Particle Swarm Optimization (PSO) and Greedy Randomized Adaptive Search Procedures (GRASP). Results are analyzed in terms of successful runs, i.e., convergence on global minimum values, and time consumption, demonstrating that FSP can achieve very good performances in most of the cases. In 90% of the cases FSP is located among the two better results as for successful runs. On the other hand, with regard to time consumption, FSP shows similar results to PSO and DE, achieving the best and second best results for 82% of the test functions. Finally, FSP showed to be a simple and robust metaheuristic that achieves good solutions for all evaluated theoretical problems. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|