@Article{cmes.2022.020744,
AUTHOR = {Qi Zhou, Jinghua Li, Ruipu Dong, Qinghua Zhou, Boxin Yang},
TITLE = {Optimization of Multi-Execution Modes and Multi-Resource-Constrained Offshore Equipment Project Scheduling Based on a Hybrid Genetic Algorithm},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {134},
YEAR = {2023},
NUMBER = {2},
PAGES = {1263--1281},
URL = {http://www.techscience.com/CMES/v134n2/49518},
ISSN = {1526-1506},
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.},
DOI = {10.32604/cmes.2022.020744}
}