In our research, we focus on these three issues, and concentrate on developing a metaheuristic framework for solving the UTRP. Embedding simple heuristic algorithms (hill-climbing and simulated annealing) within this framework, we have beaten previously best published results for Mandi’s benchmark problem, which is the only generally available data set. Due to the lack of “standard models” for the UTRP, and a shortage of benchmark data it is difficult for researchers to compare their approaches. Thus we introduce a simplified model and implement a data set generation program to produce realistic test data sets much larger than Mandi’s problem. Furthermore, some Lower Bounds and necessary constraints of the UTRP are also researched, which we use to help validate the quality of our results, particularly those obtained for our new data sets. Finally, a multi-objective optimisation algorithm is designed to solve our urban transit routing problem in which the operator’s cost is modelled in addition to passenger quality of service.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:584517 |
| Date | January 2009 |
| Creators | Fan, Lang |
| Publisher | Cardiff University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://orca.cf.ac.uk/54237/ |
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