Using Graphical Information Systems to improve vehicle routing problem instances
Hart, E. (2013). Using Graphical Information Systems to improve vehicle routing problem instances. In: (Ed.) GECCO'13 Companion, , () ( ed.). (pp. ). : . .
This paper makes the assertion that vehicle routing rearch has produced increasingly more powerful problem solvers, but has not increased the realism or compexity of typical problem instances. This paper argues that the time has come of use realistic street network data to increase the relevence and challenge of our work. A particular benefit of real world street data is the ability to support vehicle emissions modeling. Thus allowing emissions to be used as an optimisation criterion. Two on-line demonstrations are presented which demonstrate the use of GIS data obtained from Open Street Map and Google Maps. The demonstrations prove the concept that Evolutionary Algorithms may be used to solve problem instances that are based upon GIS derrived data.
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The Bio-Inspired Algorithms group within the Centre for Algorithms, Visualisation and Evolving Systems is a large and thriving group with interests in nature-inspired computing that include Evolutionary Computing, Hyper-Heuristics, Artificial Immune Systems and Swarm Intelligence.