Analysing the performance of migrating birds optimisation approaches for large scale continuous problems

Lalla-Ruiz, Eduardo; Segredo, Eduardo; Voss, Stefan; Hart, Emma; Paechter, Ben

Abstract

We present novel algorithmic schemes for dealing with large scale continuous problems. They are based on the recently proposed population-based meta-heuristics Migrating Birds Optimisation (mbo) and Multi-leader Migrating Birds Optimisation (mmbo), that have shown to be effective for solving combinatorial problems. The main objective of the current paper is twofold. First, we introduce a novel neighbour generating operator based on Differential Evolution (de) that allows to produce new individuals in the continuous decision space starting from those belonging to the current population. Second, we evaluate the performance of mbo and mmbo by incorporating our novel operator to them. Hence, mbo and mmbo are enabled for solving continuous problems. Comparisons are carried out by applying both aforementioned schemes to a set of well-known large scale functions.

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: 14th International Conference on Parallel Problem Solving from Nature (PPSN 2016)
• Start Date: Sep 17, 2016
• End Date: Sep 21, 2016
• Acceptance Date: May 30, 2016
• Online Publication Date: Aug 31, 2016
• Publication Date: 2016
• Deposit Date: May 31, 2016
• Publicly Available Date: Aug 31, 2016
• Electronic ISSN: 1611-3349
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Pages: 134-144
• Series Title: Lecture Notes in Computer Science
• Series Number: 9921
• Series ISSN: 0302-9743
• Book Title: Parallel Problem Solving from Nature – PPSN XIV
• ISBN: 978-3-319-45823-6; 978-3-319-45822-9
• DOI: https://doi.org/10.1007/978-3-319-45823-6_13
• Keywords: Migrating birds optimization; population-based meta-heuristics; MMBO (Multi-leader Migrating Birds Optimisation); global optimization problems
• Public URL: http://researchrepository.napier.ac.uk/id/eprint/10330
• Contract Date: May 31, 2016