Literature DB >> 33665695

Multi-objective location-scale optimization model and solution methods for large-scale emergency rescue resources.

Zhiqiang Li1, Chen Xie2,3, Peng Peng1, Xueying Gao4, Qingsong Wan1.   

Abstract

The location of emergency rescue resources is the basis for the supply of all kinds of materials required for rescue work. Appropriate selection of emergency resource locations can greatly improve the efficiency of emergency supplies. Based on the summary and analysis of the existing research on it, we aim to provide efficient and feasible models and solutions for the location and layout of emergency rescue resources. In optimizing the layout of emergency rescue resources, we have taken into account the dynamic characteristics of emergency demand, the needs of emergency efficiency, cost and fairness, and constructed an optimization model for emergency resource location and construction scale. At the same time, in order to reduce the scale of solving the multi-objective optimization problem under multiple disasters, improve the computational efficiency, and obtain the absolute optimal solution in the feasible region, two types of power function methods are proposed to solve the model: basic efficacy coefficient method and unit cost utility method. Finally, we design a simulation example to verify the feasibility and effectiveness of the proposed emergency resource location model and solution methods. The results show that the model proposed in this paper can maximize the effectiveness of priority emergency rescue resources, while greatly reducing emergency costs. More importantly, it can ensure the fairness of emergency rescue to a certain extent and can optimize resource scale while optimizing location. Our research will provide a practical plan reference for the configuration decision in emergency rescue work.

Entities:  

Keywords:  Emergency rescue; Environmental disaster; Location model; Multi-objective solution algorithm; Resources scale optimization

Year:  2021        PMID: 33665695     DOI: 10.1007/s11356-021-12753-9

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  1 in total

1.  Sustainable supply chain network design.

Authors:  Amir M Fathollahi-Fard; Maxim A Dulebenets; Guangdong Tian; Mostafa Hajiaghaei-Keshteli
Journal:  Environ Sci Pollut Res Int       Date:  2022-02-03       Impact factor: 4.223

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.