一种双种群协同多目标粒子群优化算法及应用

Dual-Population Cooperative Multi-objective Particle Swarm Optimization Algorithm and Its Application

针对当前我国油田开采难度大、经济效益较低等问题,建立以利润最大化为优化指标,以年度增油目标、增液目标、增注目标为约束条件的多目标油田开采优化模型,并提出一种双种群协同多目标粒子群优化算法求解该优化模型.该算法通过双种群协同进化策略扩大搜索空间,提高算法的全局搜索能力,并结合Lévy飞行保证种群多样性,提高算法收敛效率.实验结果表明,该算法能有效求解油田开采优化模型,可优选出满足目标和约束条件的结果.

Aiming at the problems of difficult oilfield exploitation and low economic efficiency in China, we established a multi-objective oilfield exploitation optimization model with profit maximization as the optimization index and annual oil-increasing target,liquid addition target and injection target.Dual-population cooperative multi-objective particle swarm optimization algorithm was used to solve the optimization model.The algorithm expanded the search space by the dualpopulation co-evolution strategy,improved the global search ability of the algorithm,and combined Lévy flight to ensure the diversity of the population and enhance the convergence efficiency of the algorithm.The experimental results show that the proposed algorithm can effectively solve the oilfield exploitation optimization model,and can optimize the results satisfying the target and constraints.