Seaside Operation Planning with Evolutionary Particle Swarm Optimization Algorithm

Document Type : Scientific - Research

Authors
Ali Omidvarvarpanah Ahmadabadi 1
Abdolreza Sheikholeslami 2
1 Master of science, Transportation Planning, School of civil engineering, Iran University of Science and Technology, Tehran, Iran
2 assistant Professor, Department of transportation Planning, School of civil engineering, Iran University of Science and Technology, Tehran, Iran
10.22119/jte.2022.314841.2570
Abstract
One of the port planning problems that has been noticed in many papers and research is the berth planning problems. Berth planning includes two sub-problems; Berth Allocation Problem (BAP) and Quay Crane Assignment Problem (QCAP). This paper develops one mathematical model by integrating these two sub-problems. The berth allocation and quay crane assignment model (BAQCAP) is solved by two metaheuristic algorithms; Taboo Search (TS) and Ant Colony Optimization (ACO). On the other hand, the berth plan is located in a disturbed environment; unexpected events may occur during the execution of the plan, making it infeasible or challenging to do the initial berth plan. These unexpected events are known as disruptions, which can impose additional costs on the port or make the initial berth plan infeasible. For this reason, The primary purpose of this paper is on the berth plan recovery in the disrupted situation. the Berth plan is recovered with two methods; Global recovery and local recovery. This paper compares global and local recovery to identify the optimal method for berth plan recovery. The numerical results show the optimal performance in the local recovery method. In this paper, the data from Shahid Rajaei port is used.

Keywords

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Quarterly Journal of Transportation Engineering
Volume 15, Issue 3 - Serial Number 60
Winter 2024
Pages 3685-3708

  • Receive Date 13 November 2021
  • Revise Date 29 December 2021
  • Accept Date 01 January 2022