Robust Optimization Research on Multi-objective Distribution of Emergency Supplies under Geological Disasters

DOI

10.2991/978-94-6463-570-6_15How to use a DOI?

Keywords

emergency supplies distribution path; robust optimization; uncertainty

Abstract

This study focuses on the emergency material distribution problem in a geologic disaster scenario, and proposes a multi-objective ant colony optimization method to plan the distribution path of rescue materials. In the event of geologic disasters, critical logistics distribution points may suffer damages, and the model proposed in this paper is dedicated to maximizing the satisfaction of the emergency rescue time while minimizing the total cost of the system, including the construction cost of the logistics facility points, the loading cost of the vehicles, the transportation cost, and the cost of the time penalty for the time window that exceeds the point of demand for the emergency supplies. To deal with this NP-Hard problem, the variability among the optimization objectives is eliminated by a percentage normalization method, and a weighting factor is introduced to balance the time satisfaction and cost.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Kai Lan
PY  - 2024
DA  - 2024/11/22
TI  - Robust Optimization Research on Multi-objective Distribution of Emergency Supplies under Geological Disasters
BT  - Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024)
PB  - Atlantis Press
SP  - 132
EP  - 141
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-570-6_15
DO  - 10.2991/978-94-6463-570-6_15
ID  - Lan2024
ER  -