Research Output

Evolving solution filtering for real-world optimisation

  Agencies who provide social care services typically have to optimise staff allocations and the travel whilst attempting to satisfy conflicting objectives. In such cases it is desirable to have a range of solutions to choose from, allowing the agency's planning staff to explore the various options available This paper examines the use of multi-objective evolutionary algorithms to produce solutions to the Workforce Scheduling and Routing Problem (WSRP) formulated with three objectives which should be minimised: financial cost, CO2 emissions and car use. We show that financial cost and CO2 increase with the size of the problem and the imposed constraints. In order to support the planning staff in their decision making, we present an Evolutionary Algorithm based support tool that will identify a group of solutions from the Pareto front which match criteria specified by the planner. We demonstrate that our approach is able to find a wide range of solutions, which enhance the flexibility of the agency’s choices, the decision support tool subsequently allows the planner to discover small groups of solutions that meet their specific requirements.

  • Date:

    20 March 2017

  • Publication Status:

    Accepted

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    006.3 Artificial intelligence

  • Funders:

    Edinburgh Napier Funded

Citation

Urquhart, N. & Fonzone, A. (in press). Evolving solution filtering for real-world optimisation. In Proceedings of the Genetic and Evolutionary Computation Conference 2017ISBN not known

Authors

Copyright

"© ACM, YYYY. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in PUBLICATION, {VOL#, ISS#, (DATE)} http://doi.acm.org/10.1145/nnnnnn.nnnnnn"

Keywords

Evolutionary Algorithms, Transportation, Multi-Objective Optimisation, Decision Support, Real-World Problems

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