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.