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Binary Bees Algorithm - bioinspiration from the foraging mechanism of honeybees to optimize a multiobjective multidimensional assignment problem

Xu, Shuo, Ji, Ze, Pham, Duc Truong and Yu, Fan 2011. Binary Bees Algorithm - bioinspiration from the foraging mechanism of honeybees to optimize a multiobjective multidimensional assignment problem. Engineering Optimization 43 (11) , pp. 1141-1159. 10.1080/0305215X.2010.542812

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Abstract

The simultaneous mission assignment and home allocation for hospital service robots studied is a Multidimensional Assignment Problem (MAP) with multiobjectives and multiconstraints. A population-based metaheuristic, the Binary Bees Algorithm (BBA), is proposed to optimize this NP-hard problem. Inspired by the foraging mechanism of honeybees, the BBA's most important feature is an explicit functional partitioning between global search and local search for exploration and exploitation, respectively. Its key parts consist of adaptive global search, three-step elitism selection (constraint handling, non-dominated solutions selection, and diversity preservation), and elites-centred local search within a Hamming neighbourhood. Two comparative experiments were conducted to investigate its single objective optimization, optimization effectiveness (indexed by the S-metric and C-metric) and optimization efficiency (indexed by computational burden and CPU time) in detail. The BBA outperformed its competitors in almost all the quantitative indices. Hence, the above overall scheme, and particularly the searching history-adapted global search strategy was validated.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Engineering
Publisher: Taylor & Francis: STM, Behavioural Science and Public Health Titles
ISSN: 0305-215X
Date of Acceptance: 9 August 2010
Last Modified: 12 Apr 2018 19:50
URI: http://orca.cf.ac.uk/id/eprint/110040

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