Multi-objective tools for the vehicle routing problem with time windows
Most real-life problems involve the simultaneous optimisation of two or more, usually conflicting, objectives. Researchers have put a continuous effort into solving these problems in many different areas, such as engineering, finance and computer science. Over time, thanks to the increase in process...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2012
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| Online Access: | https://eprints.nottingham.ac.uk/13713/ |
| _version_ | 1848791793114546176 |
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| author | Castro-Gutierrez, Juan |
| author_facet | Castro-Gutierrez, Juan |
| author_sort | Castro-Gutierrez, Juan |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Most real-life problems involve the simultaneous optimisation of two or more, usually conflicting, objectives. Researchers have put a continuous effort into solving these problems in many different areas, such as engineering, finance and computer science. Over time, thanks to the increase in processing power, researchers have created methods which have become increasingly sophisticated. Most of these methods have been based on the notion of Pareto dominance, which assumes, sometimes erroneously, that the objectives have no known ranking of importance.
The Vehicle Routing Problem with Time Windows (VRPTW) is a logistics problem which in real-life applications appears to be multi-objective. This problem consists of designing the optimal set of routes to serve a number of customers within certain time slots. Despite this problem’s high applicability to real-life domains (e.g. waste collection, fast-food delivery), most research in this area has been conducted with hand-made datasets. These datasets sometimes have a number of unrealistic features (e.g. the assumption that one unit of travel time corresponds to one unit of travel distance) and are therefore not adequate for the assessment of optimisers. Furthermore, very few studies have focused on the multi-objective nature of the VRPTW. That is, very few have studied how the optimisation of one objective affects the others.
This thesis proposes a number of novel tools (methods + dataset) to address the above- mentioned challenges: 1) an agent-based framework for cooperative search, 2) a novel multi-objective ranking approach, 3) a new dataset for the VRPTW, 4) a study of the pair-wise relationships between five common objectives in VRPTW, and 5) a simplified Multi-objective Discrete Particle Swarm Optimisation for the VRPTW. |
| first_indexed | 2025-11-14T18:34:09Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-13713 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:34:09Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-137132025-02-28T11:26:42Z https://eprints.nottingham.ac.uk/13713/ Multi-objective tools for the vehicle routing problem with time windows Castro-Gutierrez, Juan Most real-life problems involve the simultaneous optimisation of two or more, usually conflicting, objectives. Researchers have put a continuous effort into solving these problems in many different areas, such as engineering, finance and computer science. Over time, thanks to the increase in processing power, researchers have created methods which have become increasingly sophisticated. Most of these methods have been based on the notion of Pareto dominance, which assumes, sometimes erroneously, that the objectives have no known ranking of importance. The Vehicle Routing Problem with Time Windows (VRPTW) is a logistics problem which in real-life applications appears to be multi-objective. This problem consists of designing the optimal set of routes to serve a number of customers within certain time slots. Despite this problem’s high applicability to real-life domains (e.g. waste collection, fast-food delivery), most research in this area has been conducted with hand-made datasets. These datasets sometimes have a number of unrealistic features (e.g. the assumption that one unit of travel time corresponds to one unit of travel distance) and are therefore not adequate for the assessment of optimisers. Furthermore, very few studies have focused on the multi-objective nature of the VRPTW. That is, very few have studied how the optimisation of one objective affects the others. This thesis proposes a number of novel tools (methods + dataset) to address the above- mentioned challenges: 1) an agent-based framework for cooperative search, 2) a novel multi-objective ranking approach, 3) a new dataset for the VRPTW, 4) a study of the pair-wise relationships between five common objectives in VRPTW, and 5) a simplified Multi-objective Discrete Particle Swarm Optimisation for the VRPTW. 2012-12-13 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/13713/1/thesis.pdf Castro-Gutierrez, Juan (2012) Multi-objective tools for the vehicle routing problem with time windows. PhD thesis, University of Nottingham. vehicle routing problem time windows multi-objective tools transport problems transportation |
| spellingShingle | vehicle routing problem time windows multi-objective tools transport problems transportation Castro-Gutierrez, Juan Multi-objective tools for the vehicle routing problem with time windows |
| title | Multi-objective tools for the vehicle routing problem with time windows |
| title_full | Multi-objective tools for the vehicle routing problem with time windows |
| title_fullStr | Multi-objective tools for the vehicle routing problem with time windows |
| title_full_unstemmed | Multi-objective tools for the vehicle routing problem with time windows |
| title_short | Multi-objective tools for the vehicle routing problem with time windows |
| title_sort | multi-objective tools for the vehicle routing problem with time windows |
| topic | vehicle routing problem time windows multi-objective tools transport problems transportation |
| url | https://eprints.nottingham.ac.uk/13713/ |