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The Double Travelling Salesman Problem with Multiple Stacks, DTSPMS, deals with the collect and delivery of n commodities in two distinct cities, where the pickup and the delivery tours are related by LIFO constraints. During the pickup…

离散数学 · 计算机科学 2020-10-02 Laurent Alfandari , Sophie Toulouse

This work presents solutions to the Traveling Salesperson Problem with precedence constraints (TSPPC) using Deep Reinforcement Learning (DRL) by adapting recent approaches that work well for regular TSPs. Common to these approaches is the…

In this article, we present a novel formulation for the load-dependent traveling salesman problem (LD-TSP), in which travel cost (or energy expended) depends on the vehicle's current load. This problem is relevant for package delivery and…

This paper aims to develop a learning method for a special class of traveling salesman problems (TSP), namely, the pickup-and-delivery TSP (PDTSP), which finds the shortest tour along a sequence of one-to-one pickup-and-delivery nodes.…

人工智能 · 计算机科学 2024-04-18 Bowen Fang , Xu Chen , Xuan Di

We consider the online traveling salesman problem on the real line (OLTSPL) in which a salesman begins at the origin, traveling at no faster than unit speed along the real line, and wants to serve a sequence of requests, arriving online…

数据结构与算法 · 计算机科学 2025-07-10 Pei-Chuan Chen , Erik D. Demaine , Chung-Shou Liao , Hao-Ting Wei

This paper proposes a dual divide-and-optimize algorithm (DualOpt) for solving the large-scale traveling salesman problem (TSP). DualOpt combines two complementary strategies to improve both solution quality and computational efficiency.…

人工智能 · 计算机科学 2025-01-16 Shipei Zhou , Yuandong Ding , Chi Zhang , Zhiguang Cao , Yan Jin

Over the past few years, unmanned aerial vehicles (UAV), also known as drones, have been adopted as part of a new logistic method in the commercial sector called "last-mile delivery". In this novel approach, they are deployed alongside…

人工智能 · 计算机科学 2018-01-03 Quang Minh Ha , Yves Deville , Quang Dung Pham , Minh Hoàng Hà

This paper addresses the problem of energy-efficient and safe routing of last-mile electric freight vehicles. With the rising environmental footprint of the transportation sector and the growing popularity of E-Commerce, freight companies…

最优化与控制 · 数学 2024-09-24 Prateek Agarwal , Debojjal Bagchi , Tarun Rambha , Venktesh Pandey

This paper addresses the Traveling Salesman Problem with Drone (TSP-D), in which a truck and drone are used to deliver parcels to customers. The objective of this problem is to either minimize the total operational cost (min-cost TSP-D) or…

人工智能 · 计算机科学 2019-11-20 Quang Minh Ha , Yves Deville , Quang Dung Pham , Minh Hoàng Hà

In this paper, we study a dynamic pickup and delivery problem with docking constraints. There is a homogeneous fleet of vehicles to serve pickup-and-delivery requests at given locations. The vehicles can be loaded up to their capacity,…

最优化与控制 · 数学 2025-01-10 Markó Horváth , Tamás Kis , Péter Györgyi

Given a set of customers, the Flying Sidekick Traveling Salesman Problem (FSTSP) consists of using one truck and one drone to perform deliveries to them. The drone is limited to delivering to one customer at a time, after which it returns…

数据结构与算法 · 计算机科学 2024-05-30 Pedro H. D. B. Hokama , Carla N. Lintzmayer , Mário C. San Felice

This paper addresses the challenge of planning a sequence of tasks to be performed by multiple robots while minimizing the overall completion time subject to timing and precedence constraints. Our approach uses the Timed Partial Orders…

The vehicle routing problem with two-dimensional loading constraints (2L-CVRP) and the last-in-first-out (LIFO) rule presents significant practical and algorithmic challenges. While numerous heuristic approaches have been proposed to…

人工智能 · 计算机科学 2024-06-19 Yifan Xia , Xiangyi Zhang

The Dynamic Pickup and Delivery Problem (DPDP) is aimed at dynamically scheduling vehicles among multiple sites in order to minimize the cost when delivery orders are not known a priori. Although DPDP plays an important role in modern…

人工智能 · 计算机科学 2021-05-28 Xijun Li , Weilin Luo , Mingxuan Yuan , Jun Wang , Jiawen Lu , Jie Wang , Jinhu Lu , Jia Zeng

In this paper we propose some novel path planning strategies for a double integrator with bounded velocity and bounded control inputs. First, we study the following version of the Traveling Salesperson Problem (TSP): given a set of points…

机器人学 · 计算机科学 2007-05-23 Ketan Savla , Francesco Bullo , Emilio Frazzoli

We introduce the Vehicle Routing Problem with Resource-Constrained Pickup and Delivery (VRP-RPD), where vehicles transport finite identical resources to customer locations for autonomous processing before retrieval and redeployment. Unlike…

最优化与控制 · 数学 2026-03-27 Manbir Sodhi , Romesh Prasad , Harishjitu Saseendran

The Multiple Traveling Salesman Problem (MTSP) extends the traveling salesman problem by assigning multiple salesmen to visit a set of targets from a common depot, with each target visited exactly once while minimizing total tour length. A…

最优化与控制 · 数学 2026-04-28 Abhay Singh Bhadoriya , Deepjyoti Deka , Kaarthik Sundar

The Clustered Traveling Salesman Problem with a Prespecified Order on the Clusters, a variant of the well-known traveling salesman problem is studied in literature. In this problem, delivery locations are divided into clusters with…

人工智能 · 计算机科学 2018-10-10 Hoa Nguyen Phuong , Huyen Tran Ngoc Nhat , Minh Hoàng Hà , André Langevin , Martin Trépanier

The multiple Stack Travelling Salesman Problem, STSP, deals with the collect and the deliverance of n commodities in two distinct cities. The two cities are represented by means of two edge-valued graphs (G1,d2) and (G2,d2). During the…

计算复杂性 · 计算机科学 2010-09-28 Sophie Toulouse , Roberto Wolfler Calvo

Once known to be used exclusively in military domain, unmanned aerial vehicles (drones) have stepped up to become a part of new logistic method in commercial sector called "last-mile delivery". In this novel approach, small unmanned aerial…

人工智能 · 计算机科学 2018-01-03 Quang Minh Ha , Yves Deville , Quang Dung Pham , Minh Hoàng Hà
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