Dr Neil Urquhart N.Urquhart@napier.ac.uk
Lecturer
Creating optimised employee travel plans
Urquhart, Neil; Hart, Emma
Authors
Prof Emma Hart E.Hart@napier.ac.uk
Professor
Abstract
The routing of employees who provide services such as home health or social care is a complex problem. When sending an employee between two addresses , there may exist more than one travel option, e.g. public transport or car. In this paper we examine the optimisation of travel plans, supporting the provision of health and social services, with respect to objectives of travel times and estimated CO 2 produced. We include modal choice, either car or public transport as a decision variable. Car travel is normally quicker, but has a higher CO 2 cost, whereas public transport may have longer journey times, but produces less CO 2. We examine a set of problems involving real city and transport network data based in the UK cities of Edinburgh and London. We show that a multi-objective Evolutionary Algorithm can produces Pareto sets of solutions that allow a trade off between CO 2 and travel time through the use of the decision variable.
Citation
Urquhart, N., & Hart, E. (2015, September). Creating optimised employee travel plans. Presented at EuroGen 2015
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | EuroGen 2015 |
Start Date | Sep 14, 2015 |
End Date | Sep 16, 2015 |
Acceptance Date | Jun 19, 2017 |
Online Publication Date | Jul 3, 2018 |
Publication Date | 2019 |
Deposit Date | Jul 24, 2017 |
Publisher | Springer |
Pages | 489-502 |
Series Title | Computational Methods in Applied Sciences |
Series Number | 48 |
Series ISSN | 1871-3033 |
Book Title | Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences |
ISBN | 978-3-319-89986-2 |
DOI | https://doi.org/10.1007/978-3-319-89988-6_29 |
Keywords | Travel Plans, Employees, Home Health, Social Care, Travel Times, |
Public URL | http://researchrepository.napier.ac.uk/Output/965915 |
Publisher URL | https://www.springer.com/gp/book/9783319899862 |
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