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This paper delves into the Multidepot Multiple Travelling Salesman Problem (MDMTSP), an extension of the TSP that presents additional complexities. A review of the state of the art is performed, from which a MDMTSP mixed integer linear programming model is extracted. For this model, a new objective function and new variables are added to cover the need to balance the number of cities to be visited by each salesman. Various strategies are also investigated to reduce the computation times associated with the NP-Hard MDMTSP. The proposed mathematical model is not only an abstract theory, but will also be integrated into the AI-Delivery Optimiser solution of the AIDEAS project. This integration represents a step towards the manufacturing industry of the future, where artificial intelligence and process optimisation will work together to drive competitiveness and business success.

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A Model for the Multidepot Multiple Travelling Salesman Problem and Advanced Resolution Strategies

  • 会议论文

  • 发表日期：

    2025年

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  • Juan Pablo Fiesco,
  • Beatriz Andres,
  • Raul Poler

摘要

This paper delves into the Multidepot Multiple Travelling Salesman Problem (MDMTSP), an extension of the TSP that presents additional complexities. A review of the state of the art is performed, from which a MDMTSP mixed integer linear programming model is extracted. For this model, a new objective function and new variables are added to cover the need to balance the number of cities to be visited by each salesman. Various strategies are also investigated to reduce the computation times associated with the NP-Hard MDMTSP. The proposed mathematical model is not only an abstract theory, but will also be integrated into the AI-Delivery Optimiser solution of the AIDEAS project. This integration represents a step towards the manufacturing industry of the future, where artificial intelligence and process optimisation will work together to drive competitiveness and business success.