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Preemptive multi-skill resource-constrained project scheduling of marine power equipment maintenance tasks1.

Authors :
Wang, Peng
Lu, Shaojun
Cheng, Hao
Liu, Lin
Pei, Feng
Source :
Journal of Intelligent & Fuzzy Systems. 2023, Vol. 44 Issue 3, p5275-5294. 20p.
Publication Year :
2023

Abstract

The shipbuilding industry, characterized by its high complexity and remarkable comprehensiveness, deals with large-scale equipment construction, conversion, and maintenance. It contributes significantly to the development and national security of countries. The maintenance of large vessels is a complex management engineering project that presents a challenge in lowering maintenance time and enhancing maintenance efficiency during task scheduling. This paper investigates a preemptive multi-skill resource-constrained project scheduling problem and a task-oriented scheduling model for marine power equipment maintenance to address this challenge. Each task has a minimum capability level restriction during the scheduling process and can be preempted at discrete time instants. Each resource is multi-skilled, and only those who meet the required skill level can be assigned tasks. Based on the structural properties of the studied problem, we propose an improved Moth-flame optimization algorithm that integrates the opposition-based learning strategy and the mixed mutation operators. The Taguchi design of experiments (DOE) approach is used to calibrate the algorithm parameters. A series of computational experiments are carried out to validate the performance of the proposed algorithm. The experimental results demonstrate the effectiveness and validity of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10641246
Volume :
44
Issue :
3
Database :
Academic Search Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
162832466
Full Text :
https://doi.org/10.3233/JIFS-221994