An Incorporation of the Fuzzy Greedy Search Heuristic With Evolutionary Approaches for Combinatorial Optimization in Operations Management
| Autor: | Kaveh Sheibani |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Mathematical optimization
education.field_of_study 021103 operations research Heuristic (computer science) Fuzzy set Population 0211 other engineering and technologies 02 engineering and technology Fuzzy logic 0202 electrical engineering electronic engineering information engineering Combinatorial optimization 020201 artificial intelligence & image processing Greedy algorithm education Metaheuristic Greedy randomized adaptive search procedure Mathematics |
| Zdroj: | International Journal of Applied Evolutionary Computation. 8:58-72 |
| ISSN: | 1942-3608 1942-3594 |
| Popis: | Although greedy algorithms are important, nowadays it is well assumed that the solutions they obtain can be used as a starting point for more sophisticated methods. This paper describes an evolutionary approach which is based on genetic algorithms (GA). A constructive heuristic, so-called fuzzy greedy search (FGS) is employed to generate an initial population for the proposed GA. The effectiveness and efficiency of the proposed hybrid method are demonstrated on permutation flow-shop scheduling as one of the most widely studied hard combinatorial optimization problems in the area of operational research. |
| Databáze: | OpenAIRE |
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