Research on Logistics Issues in Equipment Autonomic Support
Yongle He, Na Lin, Jingtao Shang
Available Online December 2018.
- https://doi.org/10.2991/tlicsc-18.2018.85How to use a DOI?
- equipment autonomous support; material distribution; two-stage heuristic algorithm (TSHA); hybrid genetic algorithm (HGA).
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/tlicsc-18.2018.85 DO - https://doi.org/10.2991/tlicsc-18.2018.85 ID - He2018/12 ER -