Bi-level programming enabled design of an intelligent maritime search and rescue system

Lecai Cai, Yiwei Wu, Shengyan Zhu, Zheyi Tan, Wen Yi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

This paper studies an intelligent maritime search and rescue (SAR) system problem. According to historical accidents and available SAR equipment information, a bi-level mixed-integer programming (MIP) model is proposed to determine the type and number of SAR equipment allocated to activated stations. Particle swarm optimization (PSO) algorithm and genetic algorithm (GA) algorithm are applied to solve the proposed mathematical model. Computational experiments based on real instances in the East Sea China not only validate the effectiveness of the bi-level MIP model in balancing two objectives during decision process, but also indicate that PSO algorithm is better than GA algorithm to solve the proposed model and generate reasonable equipment allocation plans. Some managerial implications are also outlined on the basis of the numerical experiments.

Original languageEnglish
Article number101194
JournalAdvanced Engineering Informatics
Volume46
DOIs
Publication statusPublished - Oct 2020

Keywords

  • Bi-level
  • Equipment allocation
  • Genetic algorithm
  • Maritime search and rescue
  • Particle swarm optimization

ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence

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