A Monte Carlo tree search for traveling salesman problem with drone

Nguyen, Minh Anh; Sano, Kazushi; Tran, Vu Tu

doi:10.1016/j.eastsj.2020.100028

Cited by 10 publications

(4 citation statements)

References 16 publications

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“…A classical idea is to design a MCTS-based framework for various types of combinatorial optimization problems [31,32]. Another idea is to design a MCTS-based algorithm to solve a specific combinatorial optimization problem, such as the traveling salesman problem [33,34,35,36] and Boolean satisfiability problem [37,38,39,40]. We adopted the latter idea to find multiple optimal pivot paths for the simplex method based on MCTS.…”

Section: Combinatorial Optimization Methods Based On Mctsmentioning

confidence: 99%

Rethinking Optimal Pivoting Paths of Simplex Method

Li¹,

Li²,

Han³

et al. 2022

Preprint

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The optimal pivoting path of the simplex method is crucial for solving linear programming problems. This study proposes a new method to provide the optimal pivot and all the corresponding best pivoting paths using the Monte Carlo tree search (MCTS). First, we propose SimplexPseudoTree to transfer the simplex method into tree search mode while avoiding repeated basis variables. Based on the SimplexPseudoTree, we propose four reinforcement learning (RL) models with two actions and two rewards to make the Monte Carlo tree search suitable for the simplex method. In addition, we set a new action selection criterion to ameliorate the inaccurate evaluation in the initial exploration. We experimentally validated that the proposed schedule can avoid unnecessary searches and provide the optimal pivot. Additionally, we theoretically proved that our method determines the minimum number of pivot iterations and all corresponding optimal pivoting paths. Furthermore, this method provides the best labels for the pivot rules based on supervised learning.

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Section: Combinatorial Optimization Methods Based On Mctsmentioning

confidence: 99%

Rethinking Optimal Pivoting Paths of Simplex Method

Li¹,

Li²,

Han³

et al. 2022

Preprint

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“…The TSPRD-DR in Pina-Pardo et al [100] requires synchronization between the truck and the drone, while the VRPDR in Dayarian et al [101] does not require that. Similarly, the truck may be used for delivery only [111][112][113], as a moving depot only [114], or both [115]. Allowing the truck to act as a moving hub, in addition to fulfilling customers' orders, increases the service range of the drone [53,85].…”

Section: ) Single Truck -Single Dronementioning

confidence: 99%

“…-The truck follows the Manhattan metric while the drone follows the Euclidean distance [56,58,63,68,75,80,83,96,97,100,110,111,130,143]. In such a case, drones are assumed to be unaffected by traffic and can fly in a straight line without following the street network because they are usually faster than trucks.…”

Section: ) Model Assumptions and Parametersmentioning

confidence: 99%

“…It is proven to provide better solution quality for instances of size 100 compared to the GRASP method [31]. Nevertheless, Nguyen et al [111] applied the Monte Carlo tree search algorithm that is capable of solving instances of 200 nodes. In the TSP-mD, GRASP and Large Neighbourhood Search (LNS) metaheuristics are used [71].…”

Section: B Heuristics and Metaheuristics Solutionsmentioning

confidence: 99%

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Hybrid Truck-Drone Delivery Systems: A Systematic Literature Review

Madani

Ndiaye

2022

IEEE Access

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Owing to the continued development of e-commerce, logisticians now have an outstanding obligation to tackle last-mile delivery challenges. A number of logistics providers have suggested the incorporation of drones with trucks to provide a more flexible delivery system. This paper analyzes the content of 95 publications related to hybrid truck-drone delivery systems (HTDDS) in the context of lastmile delivery. First, a brief overview of the potential implementation of drone delivery systems is presented, including their integration with other vehicles. The overview aims to demonstrate the operational characteristics of such systems and their implications. Then, the surveyed literature is classified based on vehicles roles, system configuration, problem formulation, and solution methods. In relation to this research, several key findings and potential research directions are discussed. Despite the high level of interest in HTDDS research, it is still in its early phases and requires improvements in various areas. The payload capacity, speed, range, and energy consumption are all factors that must be considered in the modeling of drone characteristics. Almost all studies identify customer requests before the delivery operation begins. However, customer demands for immediate delivery present an opportunity for real-time optimization to provide solutions for e-commerce activities. Environmental issues are developing, as the last-mile delivery problem is regarded as the most polluting portion of the supply chain. Thus, more consideration should be given to the environmental impact of HTDDS. Finally, research on drone routing related to air traffic management has received relatively little attention.INDEX TERMS Drones, hybrid truck-drone delivery systems, last-mile delivery, routing.

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