Open Access
ARTICLE
Optimization of Multi-Execution Modes and Multi-Resource-Constrained Offshore Equipment Project Scheduling Based on a Hybrid Genetic Algorithm
Qi Zhou1,2, Jinghua Li1,3, Ruipu Dong1,*, Qinghua Zhou3,*, Boxin Yang3
1
College of Shipbuilding Engineering, Harbin Engineering University, Harbin, 150001, China
2
Shanghai Waigaoqiao Shipbuilding Co., Ltd., Shanghai, 200000, China
3
College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, 150001, China
* Corresponding Authors: Ruipu Dong. Email: ; Qinghua Zhou. Email:
(This article belongs to this Special Issue: Computer Modeling in Ocean Engineering Structure and Mechanical Equipment)
Computer Modeling in Engineering & Sciences 2023, 134(2), 1263-1281. https://doi.org/10.32604/cmes.2022.020744
Received 11 December 2021; Accepted 28 March 2022; Issue published 31 August 2022
Abstract
Offshore engineering construction projects are large and complex, having the characteristics of multiple execution
modes and multiple resource constraints. Their complex internal scheduling processes can be regarded as resourceconstrained project scheduling problems (RCPSPs). To solve RCPSP problems in offshore engineering construction
more rapidly, a hybrid genetic algorithm was established. To solve the defects of genetic algorithms, which easily fall
into the local optimal solution, a local search operation was added to a genetic algorithm to defend the offspring
after crossover/mutation. Then, an elitist strategy and adaptive operators were adopted to protect the generated
optimal solutions, reduce the computation time and avoid premature convergence. A calibrated function method
was used to cater to the roulette rules, and appropriate rules for encoding, decoding and crossover/mutation were
designed. Finally, a simple network was designed and validated using the case study of a real offshore project. The
performance of the genetic algorithm and a simulated annealing algorithm was compared to validate the feasibility
and effectiveness of the approach.
Keywords
Cite This Article
Zhou, Q., Li, J., Dong, R., Zhou, Q., Yang, B. (2023). Optimization of Multi-Execution Modes and Multi-Resource-Constrained Offshore Equipment Project Scheduling Based on a Hybrid Genetic Algorithm.
CMES-Computer Modeling in Engineering & Sciences, 134(2), 1263–1281. https://doi.org/10.32604/cmes.2022.020744