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https://doi.org/10.1177/0954410015605547

has been cited by the following article:

• TITLE: Revenue Optimization of Pipelines Construction and Operation Management Based on Quantum Genetic Algorithm and Simulated Annealing Algorithm

  AUTHORS: Kang Tan

  KEYWORDS: Quantum Genetic Algorithm, Simulated Annealing Algorithm, Pipelines Construction Management, Operation Optimization

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.6 No.6, June 14, 2018

  ABSTRACT: For the optimization of pipelines, most researchers are mainly concerned with designing the most reasonable section to meet the requirements of strength and stiffness, and at the same time reduce the cost as much as possible. It is undeniable that they do achieve this goal by using the lowest cost in design phase to achieve maximum benefits. However, for pipelines, the cost and incomes of operation management are far greater than those in design phase. Therefore, the novelty of this paper is to propose an optimization model that considers the costs and incomes of the construction and operation phases, and combines them into one model. By comparing three optimization algorithms (genetic algorithm, quantum genetic algorithm and simulated annealing algorithm), the same optimization problem is solved. Then the most suitable algorithm is selected and the optimal solution is obtained, which provides reference for construction and operation management during the whole life cycle of pipelines.