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. A set of well-known large scale functions is used for comparison purposes.
CITATION STYLE
Lalla-Ruiz, E., Segredo, E., Voß, S., Hart, E., & Paechter, B. (2016). Analysing the performance of migrating birds optimisation approaches for large scale continuous problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9921 LNCS, pp. 134–144). Springer Verlag. https://doi.org/10.1007/978-3-319-45823-6_13
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