Title: Research on multi-task allocation and path optimisation for offshore wind farm inspection based on GDE-ABC algorithm and TM-MTSP

Authors: Xiangfeng Kong; Mengfei Xu; Lei Kou; Benfa Zhang; Fangfang Zhang; Quande Yuan; Zhen Yu

Addresses: State Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao, 266300, China ' State Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao, 266300, China ' State Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao, 266300, China ' State Grid Songyuan Power Supply Company, Songyuan, 138001, China ' State Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao, 266300, China ' School of Computer Technology and Engineering, Changchun Institute of Technology, Changchun, 130103, China ' State Key Laboratory of Physical Oceanography, Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao, 266300, China; Modern Precision Measurement and Laser Non-destructive Testing Key Laboratory of Higher Education in Fujian Province, Putian University, Putian, 351100, China

Abstract: Offshore wind farm inspection includes various tasks and vessels, so task assignment and path planning form a complex combinatorial optimisation problem. Efficient solutions are essential to improve efficiency and reduce costs. This paper applies the task matching multiple travelling salesmen problem (TM-MTSP) to offshore wind farm inspection and proposes a novel greedy dynamic elite artificial bee colony algorithm (GDE-ABC) for scheduling multiple inspection vessels. The objective is to minimise the maximum inspection time. A greedy strategy with task constraints is used to generate initial solutions. The algorithm balances exploration and exploitation by using dynamic retention probability-based neighbourhood search and tournament selection. Simulation results show that the proposed GDE-ABC is effective. Compared with traditional algorithms, it significantly shortens the maximum inspection time, improves operation and maintenance efficiency, and reduces related costs.

Keywords: GDE-ABC algorithm; TM-MTSP; inspection task scheduling; offshore wind farm; path planning; multi-vessel scheduling.

DOI: 10.1504/IJCSM.2026.154304

International Journal of Computing Science and Mathematics, 2026 Vol.23 No.2, pp.147 - 164

Received: 18 Nov 2025
Accepted: 27 Feb 2026
Published online: 19 Jun 2026 *

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