New heuristics and meta-heuristics for the Bandpass problem
| Autor: | Hakan Kutucu, Arif Gursoy, Mehmet Kurt, Urfat Nuriyev |
|---|---|
| Přispěvatelé: | Ege Üniversitesi |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Heuristic and meta-heuristic algorithms
Computer Networks and Communications Computer science Heuristic (computer science) Population Crossover 0211 other engineering and technologies 0102 computer and information sciences 02 engineering and technology 01 natural sciences Biomaterials Combinatorial optimization problem Wavelength-division multiplexing education Metaheuristic Implementation Civil and Structural Engineering Fluid Flow and Transfer Processes education.field_of_study 021103 operations research Mechanical Engineering Metals and Alloys Electronic Optical and Magnetic Materials Cost reduction Bandpass problem 010201 computation theory & mathematics Hardware and Architecture lcsh:TA1-2040 Wavelength division multiplexing Boolean programming Heuristics lcsh:Engineering (General). Civil engineering (General) Algorithm |
| Zdroj: | Engineering Science and Technology, an International Journal, Vol 20, Iss 6, Pp 1531-1539 (2017) |
| ISSN: | 2215-0986 |
| Popis: | WOS: 000428053200003 The Bandpass problem (BP), modelled by Babayev et al., is a combinatorial optimization problem arising in optical communication networks using wavelength division multiplexing technology. The BP aims to design an optimal packing of information flows on different wavelengths into groups to obtain the highest available cost reduction. In this paper, we propose new methods to solve the BP. Firstly, we present two new heuristic algorithms which generate better solutions than the algorithm introduced by Babayev et al. for almost all of the problem instances of the BP library. Secondly, we present a new meta-heuristic algorithm using three different crossover and five different mutation operators. Totally, fifteen implementations have been created and tested using two different outputs which are obtained by our proposed heuristics as the initial population. The experimental results show that the proposed meta-heuristic algorithm improves the solutions. (C) 2017 Karabuk University. Publishing services by Elsevier B.V. Scientific and Technological Research Council of Turkey-TUBITAK 3001 Project [114F073] The authors would like to thank the anonymous referees for their valuable comments that considerably improved the presentation of the paper. This work is supported by the Scientific and Technological Research Council of Turkey-TUBITAK 3001 Project (Project No.: 114F073). |
| Databáze: | OpenAIRE |
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