University of Hertfordshire Research Archive

        JavaScript is disabled for your browser. Some features of this site may not work without it.

        Browse

        All of UHRABy Issue DateAuthorsTitlesThis CollectionBy Issue DateAuthorsTitles

        Arkivum Files

        My Downloads
        View Item 
        • UHRA Home
        • University of Hertfordshire
        • Research publications
        • View Item
        • UHRA Home
        • University of Hertfordshire
        • Research publications
        • View Item

        Bio-inspired binary bees algorithm for a two-level distribution optimisation problem

        Author
        Xu, S.
        Ji, Z
        Pham, D.T.
        Yu, F.
        Attention
        2299/5732
        Abstract
        Two uncoupleable distributions, assigning missions to robots and allocating robots to home stations, accompany the use of mobile service robots in hospitals. In the given problem, two workload-related objectives and five groups of constraints are proposed. A bio-mimicked Binary Bees Algorithm (BBA) is introduced to solve this multiobjective multiconstraint combinatorial optimisation problem, in which constraint handling technique (Multiobjective Transformation, MOT), multiobjective evaluation method (nondominance selection), global search strategy (stochastic search in the variable space), local search strategy (Hamming neighbourhood exploitation), and post-processing means (feasibility selection) are the main issues. The BBA is then demonstrated with a case study, presenting the execution process of the algorithm, and also explaining the change of elite number in evolutionary process. Its optimisation result provides a group of feasible nondominated two-level distribution schemes.
        Publication date
        2010
        Published in
        Journal of Bionic Engineering
        Published version
        https://doi.org/10.1016/S1672-6529(09)60205-5
        Other links
        http://hdl.handle.net/2299/5732
        Metadata
        Show full item record
        Keep in touch

        © 2019 University of Hertfordshire

        I want to...

        • Apply for a course
        • Download a Prospectus
        • Find a job at the University
        • Make a complaint
        • Contact the Press Office

        Go to...

        • Accommodation booking
        • Your student record
        • Bayfordbury
        • KASPAR
        • UH Arts

        The small print

        • Terms of use
        • Privacy and cookies
        • Criminal Finances Act 2017
        • Modern Slavery Act 2015
        • Sitemap

        Find/Contact us

        • T: +44 (0)1707 284000
        • E: ask@herts.ac.uk
        • Where to find us
        • Parking
        • hr
        • qaa
        • stonewall
        • AMBA
        • ECU Race Charter
        • disability confident
        • AthenaSwan