Hybrid Genetic Algorithm for Topology and Layout Optimization of Oilfield Water Injection System
Yang Liu
Abstract
Yang Liu
Abstract
An optimization model of topology and layout optimization for water injection system is established,in which the minimum investment is taken as objective function.According to the model characteristics,the problem is divided into two layers,the genetic algorithm and nonlinear optimization are used to solve.The operational process of genetic algorithm is improved,the fitness function is adjusted,the cross and mutation method are improved,simulated annealing algorithm is combined with,and restrictions are satisfied,infeasible solutions are reduced,optimum performance of genetic algorithm is enhanced.Optimization results show that the algorithm is efficient.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
An optimization model of topology and layout optimization for water injection system is established,in which the minimum investment is taken as objective function.According to the model characteristics,the problem is divided into two layers,the genetic algorithm and nonlinear optimization are used to solve.The operational process of genetic algorithm is improved,the fitness function is adjusted,the cross and mutation method are improved,simulated annealing algorithm is combined with,and restrictions are satisfied,infeasible solutions are reduced,optimum performance of genetic algorithm is enhanced.Optimization results show that the algorithm is efficient.
Key concepts: Mathematical optimization, Simulated annealing, Genetic algorithm, Meta-optimization, Computer science, Fitness function, Topology optimization, Algorithm