Affiliation:
1. College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China
2. College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China
Abstract
In order to complete the offshore platform project scheduling intelligently, an improved scheduling optimization system based on the parallel genetic algorithm was proposed. An optimal model for the large-scale offshore platform project scheduling problem (LSOPPSP) was built and produced the mathematic model of LSOPPSP, based on the characteristics of the abundance of activities, long duration, high uncertainty, and frequent changes. In long-term unsteady manufacturing, this model can provide good robustness. In addition, the essential steps of the multitime window parallel genetic algorithm were proposed. An improved population initialization algorithm was designed, as well as the coevolution strategy among populations was also proposed in parallel computing. These two strategies can increase population variety while also speeding up convergence. Finally, the suggested parallel scheduling system was deployed in our self-developed schedule optimization software for offshore platform enterprises, and the outperformance of the improved algorithm was proven by simulated examples and practical application.
Funder
Ministry of Industry and Information Technology of the People's Republic of China
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems
Cited by
1 articles.
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