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Modelling of Taxi Dispatch Problem Using Heuristic Algorithms

  • Mateusz Adamczyk
  • Dariusz KrólEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 833)

Abstract

Taxi routing is a complex task that involves the pickup and delivery by a fleet of vehicles in a specified time, taking into account many parameters and criteria. This paper describes issues related to this problem. It proposes a formal description of the problem and a goal function using a wide variety of criteria. Three heuristic algorithms: Ant Colony Optimization, Artificial Bee Colony and Genetic Algorithm are selected for testing. As a result three variants of these algorithms are implemented: Ant Colony System (ACS), Predict and Select - Artificial Bee Colony (PS-ABC) and Genetic Algorithm (GA) to conduct a survey. Operators used in the algorithms are adapted to a taxi dispatch problem. The analysis is performed in order to find the best parameters for the algorithms according to the data input. Finally, the efficiency of the algorithms are compared in order to determine the best algorithm. In several experiments the Ant Colony System outperforms any other algorithm presented here with respect to taxi working time currently in service.

Keywords

Evolutionary computation Real world applications Vehicle routing Collective decision Reinforcement learning Fleet management 

Notes

Acknowledgments

The authors acknowledge the support from the statutory funds of the Wrocław University of Science and Technology.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Computer Science and ManagementWrocław University of Science and TechnologyWrocławPoland
  2. 2.Department of Information Systems, Faculty of Computer Science and ManagementWrocław University of Science and TechnologyWrocławPoland

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