## Abstract

The hazardous material transportation requires extensive care owing to the disastrous consequences of accidents, such as chemical spills or radioactive exposures. Consequently, a minimum risk delivery plan that is dynamically decided by the cargo load of the vehicle at each customer must be scheduled. We introduce a traveling salesman problem (TSP) with a sequence-and-load dependent risk, which differs from the conventional TSP as the arc costs are determined by the hazardous cargo load at each decision epoch. We define our problem in a dynamic programming formulation and present mixed-integer linear program with a nonlinear objective function. To efficiently retrieve exact optimal solutions, we propose an iterative-deepening A*-based tree search algorithm using admissible lower and efficient upper bound algorithms for guaranteed optimality. Numerical experiments indicate that the proposed algorithm outperforms a current state-of-the-art solver. An ablation study and sensitivity analysis demonstrate the effectiveness of the proposed algorithm and derive managerial insights.

Original language | English |
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Pages (from-to) | 1-18 |

Number of pages | 18 |

Journal | IEEE Transactions on Intelligent Transportation Systems |

DOIs | |

Publication status | Accepted/In press - 2024 |

### Bibliographical note

Publisher Copyright:IEEE

## Keywords

- Hazardous material delivery
- iterative deepening A*
- traveling salesman problem

## ASJC Scopus subject areas

- Automotive Engineering
- Mechanical Engineering
- Computer Science Applications