Energy-constrained multi-visit TSP with multiple drones considering non-customer rendezvous locations

会合 无人机 计算机科学 能量(信号处理) 旅行商问题 运筹学 数学优化 航空航天工程 数学 算法 统计 工程类 航天器 生物 遗传学
作者
Bahare Mahmoudi,Kourosh Eshghi
出处
期刊:Expert Systems With Applications [Elsevier]
卷期号:210: 118479-118479 被引量:14
标识
DOI:10.1016/j.eswa.2022.118479
摘要

• We study a multi-visit traveling salesman problem with multiple drones. • Drone energy consumption in all phases of flight is considered to plan drone trips. • We propose a subproblem to locate candidate non-customer retrieval nodes for drones. • MILP formulations are developed for the proposed subproblem and problem. • Effective heuristic and matheuristic solution approaches are provided for problems. This paper introduces the energy-constrained multi-visit traveling salesman problem with multiple drones considering non-customer rendezvous locations (EM-TSPDs). A ground vehicle equipped with multiple drones that can serve multiple customers per trip performs deliveries. Before solving the EM-TSPDs, the non-customer rendezvous location subproblem (NRLP) is addressed to locate candidate non-customer rendezvous nodes so that all drone customers can be covered by drones. The importance of this full coverage is that all drone customers can reap the benefits of drone delivery by receiving fast delivery or being served in areas that are inaccessible by road network. We propose MILP formulations for the NRLP and EM-TSPDs that can be solved with standard MILP solvers. Due to the NP-hard nature of the problem, heuristic algorithms are provided to solve medium and large-scale instances in a time-efficient manner. Numerical results show that using multiple drones that can serve multiple customers per trip leads to a reduction in the makespan. Taking into account the battery energy consumption at different phases of the drone flight leads to more accurate and realistic modeling of the drone endurance. In addition, the impact of adding non-customer rendezvous locations is investigated.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
无限的千凝完成签到 ,获得积分10
刚刚
丘比特应助小侯采纳,获得10
刚刚
完美世界应助oldblack采纳,获得10
刚刚
1秒前
霍笑寒完成签到,获得积分10
1秒前
积极的雅寒完成签到 ,获得积分10
1秒前
1秒前
2秒前
俊逸的草莓完成签到,获得积分10
2秒前
3秒前
4秒前
英姑应助www采纳,获得10
4秒前
WFZ发布了新的文献求助10
5秒前
田様应助娜娜采纳,获得10
5秒前
ZXY完成签到,获得积分10
5秒前
5秒前
LINGXINYUE完成签到,获得积分10
6秒前
酷波er应助壮观手套采纳,获得10
7秒前
折耳根拌香菜完成签到,获得积分10
8秒前
9秒前
l900完成签到,获得积分10
9秒前
凡F完成签到 ,获得积分10
10秒前
奶茶一天一杯完成签到,获得积分10
10秒前
侯赛雷完成签到,获得积分10
10秒前
11秒前
11秒前
多情山蝶发布了新的文献求助10
12秒前
YC完成签到 ,获得积分10
13秒前
fa完成签到,获得积分10
13秒前
风吹似夏完成签到,获得积分10
13秒前
疯狂加载ing应助宁平凡采纳,获得50
13秒前
叶子发布了新的文献求助10
14秒前
Hello应助食量大如牛采纳,获得10
14秒前
啦啦啦啦啦完成签到 ,获得积分10
14秒前
你嵙这个期刊没买应助l900采纳,获得20
15秒前
15秒前
Joy发布了新的文献求助10
16秒前
稳重幻珊完成签到 ,获得积分10
17秒前
farah完成签到 ,获得积分10
17秒前
17秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 3000
Terrorism and Power in Russia: The Empire of (In)security and the Remaking of Politics 1000
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6044839
求助须知:如何正确求助?哪些是违规求助? 7813516
关于积分的说明 16246324
捐赠科研通 5190514
什么是DOI,文献DOI怎么找? 2777408
邀请新用户注册赠送积分活动 1760631
关于科研通互助平台的介绍 1643782