An Adaptive Ant Colony System Based on Variable Range Receding Horizon Control for Berth Allocation Problem

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

8 Scopus Citations
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Author(s)

  • Rong Wang
  • Fei Ji
  • Yi Jiang
  • Sheng-Hao Wu
  • Jun Zhang
  • Zhi-Hui Zhan

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)21675-21686
Journal / PublicationIEEE Transactions on Intelligent Transportation Systems
Volume23
Issue number11
Online published18 May 2022
Publication statusPublished - Nov 2022

Link(s)

Abstract

The berth allocation problem (BAP) is an NP-hard problem in maritime traffic scheduling that significantly influences the operational efficiency of the container terminal. This paper formulates the BAP as a permutation-based combinatorial optimization problem and proposes an improved ant colony system (ACS) algorithm to solve it. The proposed ACS has three main contributions. First, an adaptive heuristic information (AHI) mechanism is proposed to help ACS handle the discrete and real-time difficulties of BAP. Second, to relieve the computational burden, a divide-and-conquer strategy based on variable-range receding horizon control (vRHC) is designed to divide the complete BAP into a set of sub-BAPs. Third, a partial solution memory (PSM) mechanism is proposed to accelerate the ACS convergence process in each receding horizon (i.e., each sub-BAP). The proposed algorithm is termed as adaptive ACS (AACS) with vRHC strategy and PSM mechanism. The performance of the AACS is comprehensively tested on a set of test cases with different scales. Experimental results show that the effectiveness and robustness of AACS are generally better than the compared state-of-the-art algorithms, including the well-performing adaptive evolutionary algorithm and ant colony optimization algorithm. Moreover, comprehensive investigations are conducted to evaluate the influences of the AHI mechanism, the vRHC strategy, and the PSM mechanism on the performance of the AACS algorithm.

Research Area(s)

  • Containers, Resource management, Optimization, Companies, Cranes, Aircraft, Processor scheduling, Berth allocation problem (BAP), ant colony system (ACS), evolutionary computation (EC), variable-range receding horizon control, adaptive heuristic information, DISCRETE, ASSIGNMENT, ALGORITHM, SEARCH

Citation Format(s)

An Adaptive Ant Colony System Based on Variable Range Receding Horizon Control for Berth Allocation Problem. / Wang, Rong; Ji, Fei; Jiang, Yi et al.
In: IEEE Transactions on Intelligent Transportation Systems, Vol. 23, No. 11, 11.2022, p. 21675-21686.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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