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Evolving Cuckoo Search: From single-objective to multi-objective
University of Skövde, School of Technology and Society.
2011 (English)Independent thesis Advanced level (degree of Master (One Year)), 15 credits / 22,5 HE creditsStudent thesis
Abstract [en]

This thesis aims to produce a novel multi-objective algorithm that is based on Cuckoo Search by Dr. Xin-She Yang. Cuckoo Search is a promising nature-inspired meta-heuristic optimization algorithm, which currently is only able to solve single-objective optimization problems. After an introduction, a number of theoretical points are presented as a basis for the decision of which algorithms to hybridize Cuckoo Search with. These are then reviewed in detail and verified against current benchmark algorithms to evaluate their efficiency.

To test the proposed algorithm in a new setting, a real-world combinatorial problem is used. The proposed algorithm is then used as an optimization engine for a simulation-based system and compared against a current implementation. 

Place, publisher, year, edition, pages
2011. , 53 p.
Keyword [en]
cuckoo search, evolutionary algorithms, meta-heuristic optimization algorithm
National Category
URN: urn:nbn:se:his:diva-5309OAI: diva2:445763
Subject / course
Automation Engineering
Educational program
Industrial Informatics - Master's Programme
Available from: 2012-11-14 Created: 2011-10-05 Last updated: 2012-11-14Bibliographically approved

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fulltext(1983 kB)1203 downloads
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Lidberg, Simon
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