Introductory Chapter: Advances in Logistics Engineering DOI

Ágota Bányai

IntechOpen eBooks, Год журнала: 2024, Номер unknown

Опубликована: Окт. 2, 2024

Язык: Английский

Fleet resupply by drones for last-mile delivery DOI
Juan C. Pina-Pardo, Daniel F. Silva, Alice E. Smith

и другие.

European Journal of Operational Research, Год журнала: 2024, Номер 316(1), С. 168 - 182

Опубликована: Фев. 2, 2024

Язык: Английский

Процитировано

8

Locating charging stations and routing drones for efficient automated stocktaking DOI Creative Commons
Panupong Vichitkunakorn, Simon Emde, Makusee Masae

и другие.

European Journal of Operational Research, Год журнала: 2024, Номер 316(3), С. 1129 - 1145

Опубликована: Март 2, 2024

Drones have received growing attention in logistics recently. One possible application is deploying drones for auditing inventory warehouses. With the use of drones, warehouses are able to increase record accuracy and decrease labor costs. In this research, we introduce stocktaking drone routing problem (STDRP), which consists a fleet through warehouse purposes as well deciding on location charging stations floor, necessary due limited battery capacity drones. Subsequently, develop an adaptive large neighbourhood search-based heuristic (ALNS) with novel solution encoding decoding approaches solve STDRP. numerical study, show that ALNS can realistic instances reasonable time. We also derive recommendations regarding ideal size fleet, infrastructure, capacity. Finally, investigate interplay between storage assignment policy (such popular ABC rule) efficiency using

Язык: Английский

Процитировано

8

Facility location decisions for drone delivery with riding: A literature review DOI Creative Commons
Okan Dükkancı, James F. Campbell, Bahar Y. Kara

и другие.

Computers & Operations Research, Год журнала: 2024, Номер 167, С. 106672 - 106672

Опубликована: Апрель 18, 2024

This study presents a comprehensive literature survey on facility location problems for drone (uncrewed vehicle) delivery in situations where drones can ride or other vehicles. includes facilities visited by only one type of vehicle, as well both and Unlike traditional systems with vehicle type, hybrid vehicle-drone usually require determining locations the two types meet separate. The main goals this paper are to review large volume riding from perspective provide connection between studies different research areas that cover similar problems, highlight future directions area. We first functions drones, including aerial ground used systems. is categorized based presence resupply operations, launch retrieval points, (aerial ground) space (discrete continuous). Each category analyzed terms modeling approach, decision(s), objective function(s), constraints additional features. concludes promising directions.

Язык: Английский

Процитировано

6

Optimal drone deployment for cost‐effective and sustainable last‐mile delivery operations DOI Creative Commons
Gaurav Kumar,

Oqais Tanvir,

Akhilesh Kumar

и другие.

International Transactions in Operational Research, Год журнала: 2024, Номер unknown

Опубликована: Авг. 9, 2024

Abstract Delivery by drones holds significant potential to solve issues (such as high costs, access remote areas, etc.) faced in last‐mile delivery operations, particularly the e‐commerce industry. Still, it involves complex such multi‐trip energy estimation, and battery recharge planning. A sound drone problem entails an optimal deployment plan with routing details at lowest possible cost. To this end, study focuses on formulating a that routing, optimization, travel time optimization problems where consumption is modeled non‐linear function. We develop mixed integer programming model integrated model. This aims to: (a) maximize revenue meeting demand completely without leaving idle drones, (b) optimize use (c) minimize required fleet size for plan. The proposed solved using Gurobi Solver, which employs data supplied well‐known firm. introduce two‐phase heuristic solution methodology tackle larger networks’ complexities. method consists of clustering phase (K‐means method) phase. robustness developed mathematical modeling demonstrated testing varied large instances. evaluation shows expanding destination options boosts until saturation, necessitating more drones. Efficient route planning adjustments are crucial rising satisfying customers amidst dense clustering. helps manage daily deliveries anticipate future growth.

Язык: Английский

Процитировано

5

An exact method and a heuristic for last-mile delivery drones routing with centralized graph-based airspace control DOI
Jorge Luiz Franco, Vitor Curtis, Edson Luiz França Senne

и другие.

Computers & Operations Research, Год журнала: 2025, Номер unknown, С. 107006 - 107006

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Integrating battery-related decisions into truck-drone tandem delivery problem with limited battery resources DOI
Zhongshan Liu, Bin Yu, Tingting Chen

и другие.

Transportation Research Part C Emerging Technologies, Год журнала: 2025, Номер 174, С. 105082 - 105082

Опубликована: Март 17, 2025

Язык: Английский

Процитировано

0

A Survey of Approximation Algorithms for the Universal Facility Location Problem DOI Creative Commons

Xiao Hua-xing,

Jiaming Zhang,

Zhikang Zhang

и другие.

Mathematics, Год журнала: 2025, Номер 13(7), С. 1023 - 1023

Опубликована: Март 21, 2025

The facility location problem is a classical combinatorial optimization with extensive applications spanning communication technology, economic management, traffic governance, and public services. to assign set of clients facilities such that each client connects the total cost (open connection cost) as low possible. Among its various models, uncapacitated (UFL) most fundamental widely studied. However, in real-world scenarios, resource constraints often make UFL insufficient, necessitating more generalized models. This investigation primarily focuses on universal (Uni-FL) problem, framework encompassing both capacitated problems (with hard soft capacity constraints) problem. Through systematic analysis, we examine Uni-FL alongside specialized variants: (HCFL) (SCFL) A comprehensive survey conducted existing approximation algorithms theoretical results. relevant results their important variants are also discussed. In addition, propose some open questions future research directions for this based research.

Язык: Английский

Процитировано

0

A multi-objective adaptive memetic algorithm and engineering application for a double-floor layout problem with separate human and vehicle transport elevators DOI

Dan Ji,

Zeqiang Zhang, Minjie Zhao

и другие.

Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 155, С. 111010 - 111010

Опубликована: Май 12, 2025

Язык: Английский

Процитировано

0

LumiLoc: A Low-Light-Optimized Visual Localization Framework for Autonomous Drones DOI Creative Commons
Ruokun Qu,

Z. Wang,

Yelu Liu

и другие.

Aerospace, Год журнала: 2025, Номер 12(6), С. 454 - 454

Опубликована: Май 22, 2025

In low-light conditions, UAV localization faces substantial challenges due to reduced visibility, elevated noise levels, and diminished contrast. To address these issues, we propose a low-light-optimized visual framework that integrates an attention-based image enhancement module, robust feature extraction network tailored for degraded environments, lightweight pose estimation algorithm fuses geometric convolutional features. Extensive evaluations on both real-world synthetic datasets reveal significant improvements in accuracy, resilience, adaptability dynamic lighting. Moreover, experimental results validate the framework’s feasibility applications night operations, urban air traffic management, disaster response, thereby effectively overcoming critical limitations of positioning under conditions.

Язык: Английский

Процитировано

0

Path pool based transformer model in reinforcement framework for dynamic urban drone delivery problem DOI Creative Commons
Zhibin Wu, Yanfang Mo, Wei Liu

и другие.

Transportation Research Part C Emerging Technologies, Год журнала: 2025, Номер 177, С. 105165 - 105165

Опубликована: Июнь 2, 2025

Язык: Английский

Процитировано

0