Research on Logistics Issues in Equipment Autonomic Support

DOI

10.2991/tlicsc-18.2018.85How to use a DOI?

Keywords

equipment autonomous support; material distribution; two-stage heuristic algorithm (TSHA); hybrid genetic algorithm (HGA).

Abstract

This paper studies the typical logistics problem in equipment support, i.e. the decision-making optimization of material supply, which refers specifically to the transportation and distribution of materials and equipment (such as ammunition, oil, personnel, medical supplies, maintenance accessories, maintenance equipment, etc.) during the replenishment process. Firstly, we model the problem as a multi-depot vehicle routing problem (MDVRP), and then design a two-stage heuristic algorithm to solve it. We construct an example of 150 demand points and 3 resource points to validate the effectiveness of the algorithm, and compare the two-stage heuristic algorithm with the simulated annealing-based particle swarm optimization (SAPSO) algorithm. The experimental results show that the two-stage heuristic algorithm can better solve the logistics problem in equipment autonomic support.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yongle He
AU  - Na Lin
AU  - Jingtao Shang
PY  - 2018/12
DA  - 2018/12
TI  - Research on Logistics Issues in Equipment Autonomic Support
BT  - Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
PB  - Atlantis Press
SP  - 524
EP  - 529
SN  - 1951-6851
UR  - https://doi.org/10.2991/tlicsc-18.2018.85
DO  - 10.2991/tlicsc-18.2018.85
ID  - He2018/12
ER  -