A Hybrid Brain Storm Optimization Algorithm to Solve the Emergency Relief Routing Model

Xuming Wang, Jiaqi Zhou, Xiaobing Yu () and Xianrui Yu
Additional contact information
Xuming Wang: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Jiaqi Zhou: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Xiaobing Yu: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Xianrui Yu: School of Management and Engineering, Beihang University, Beijing 100191, China

Sustainability, 2023, vol. 15, issue 10, 1-31

Abstract: Due to the inappropriate or untimely distribution of post-disaster goods, many regions did not receive timely and efficient relief for infected people in the coronavirus disease outbreak that began in 2019. This study develops a model for the emergency relief routing problem (ERRP) to distribute post-disaster relief more reasonably. Unlike general route optimizations, patients’ suffering is taken into account in the model, allowing patients in more urgent situations to receive relief operations first. A new metaheuristic algorithm, the hybrid brain storm optimization (HBSO) algorithm, is proposed to deal with the model. The hybrid algorithm adds the ideas of the simulated annealing (SA) algorithm and large neighborhood search (LNS) algorithm into the BSO algorithm, improving its ability to escape from the local optimum trap and speeding up the convergence. In simulation experiments, the BSO algorithm, BSO+LNS algorithm (combining the BSO with the LNS), and HBSO algorithm (combining the BSO with the LNS and SA) are compared. The results of simulation experiments show the following: (1) The HBSO algorithm outperforms its rivals, obtaining a smaller total cost and providing a more stable ability to discover the best solution for the ERRP; (2) the ERRP model can greatly reduce the level of patient suffering and can prioritize patients in more urgent situations.

Keywords: relief routing; BSO algorithm; hybrid algorithms; route optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/10/8187/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/10/8187/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:10:p:8187-:d:1149565

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().