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Route prioritisation in a multi-agent transportation environment via multi-attribute decision making

Author

Listed:
  • Adil Baykasoglu
  • Vahit Kaplanoglu
  • Cenk Sahin

Abstract

Effective management of the vehicles plays an important role in transportation sector. There are some novel approaches in software engineering which can be used to dynamically control the trucks. One of the example technologies is multi-agent systems. Multi-agent-based technologies could be used for truck dispatching in real time. The trucks in such systems have their own transportation plan and they can decide about their routes throughout their operations. Any truck agent must select a route to pickup or deliver a transportation order while doing its transportation operation. However, truck driver route preference is also crucial for the transportation performances because of morale, motivation and psychological conditions of drivers have a considerable effect on transportation operation success. In this paper, driver route preference model is incorporated into a multi-agent-based vehicle dispatching system which uses fuzzy graph theoretical-matrix permanent approach which is a novel method in multi-attribute decision making (MADM). The model is also compared with fuzzy TOPSIS method. Spearman rank correlation test is used to assess the correlation between the ranks.

Suggested Citation

  • Adil Baykasoglu & Vahit Kaplanoglu & Cenk Sahin, 2016. "Route prioritisation in a multi-agent transportation environment via multi-attribute decision making," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 8(1), pages 47-64.
    • Handle: RePEc:ids:injdan:v:8:y:2016:i:1:p:47-64
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    References listed on IDEAS

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