NDLI: Variable mesh optimization for the 2013 CEC Special Session Niching Methods for Multimodal Optimization

Content Provider	IEEE Xplore Digital Library
Author	Molina, D. Puris, A. Bello, R. Herrera, F.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci. & Artificial Inteligence, Univ. of Granada, Granada, Spain (Herrera, F.) \|\| Dept. of Comput. Sci., Univ. of Las Villas, Cuba (Puris, A.; Bello, R.) \|\| Dept. of Comput. Sci. & Eng., Univ. of Cadiz, Cadiz, Spain (Molina, D.)
Abstract	Many real-world problems have several optima, and the aim of niching optimisation algorithms is to obtain the different global optima, and not only the best solution. One common technique to create niches is the clearing method that removes solutions too close to better ones. Unfortunately, clearing is very sensitive to the niche radius, and its right value depends on the problem (in real-world problems the minimum distance between optima is unknown). In this work we propose a niching algorithm that uses clearing with an adaptive niche radius, that decreases during the run. The proposal uses an external memory that stores current global optima to avoid losing found optima during the clearing process, allowing a non-elitist search. This algorithm applies this clearing method to a mesh of solutions, expanded by the generation of nodes using combination methods between the nodes, their best neighbour, and their nearest current global optima in the population (current global optima are nodes with fitness very similar to current best fitness). The proposal is tested on the competition benchmark proposed in the Special Session Niching Methods for Multimodal Optimization, and compared with other algorithms. The proposal obtains very good results detecting global optima. In comparisons with other algorithm, this proposal obtains the best results, proving to be a very competitive niching algorithm.
Starting Page	87
Ending Page	94
File Size	826821
Page Count	8
File Format	PDF
ISBN	9781479904532
e-ISBN	9781479904549
e-ISBN	9781479904525
DOI	10.1109/CEC.2013.6557557
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-20
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sociology Statistics Optimization Equations Proposals Benchmark testing Euclidean distance continuous optimisation niching optimisation evolutionary algorithms
Content Type	Text
Resource Type	Article

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