基于记忆分子动理论多目标优化算法的经济环境调度

The Economic Environment Dispatch Based on Multi-Objective Memory Kinetic-Molecular Theory Optimization Algorithm

针对电力系统经济调度问题的多目标特性,提出一种记忆分子动理论多目标优化算法(Multi-objective MemoryKinetic-MoleculartheoryOptimizationAlgorithm,MOMKMTOA)。该算法在分子动理论算法(Kinetic-Molecular theory Optimization Algorithm, KMTOA)的基础上引入记忆原理记忆,设计记忆更新与遗忘模型以提高算法的多样性,并提出记忆精英选择策略从当代解集中随机选择领导精英以避免陷入局部最优。通过CEC09标准测试函数和IEEE-30节点的两个案例验证说明,MOMKMTOA算法在求解高维复杂的多目标经济调度问题上具有一定的可行性和有效性。

Multi-Objective memory Kinetic-Molecular Theory Optimization Algorithm(MOMKMTOA) is proposed to solve the multi-objective characteristics of power system economic dispatching problem.To improve the diversity of the algorithm,the updated operator of memory and the forgotten operator of memory based on Kinetic-Molecular theory Optimization Algorithm(KMTOA) is designed.To avoid falling into local optimum,the selection strategy of leading elite which randomly select the leader from the first-level memory frontier is proposed.Test function of CEC09 and two cases of IEEE-30 nodes show that MOMKMTOA algorithm is feasible and effective in solving multi-objective economic dispatching problems with high-dimensional complexity.