混合策略的沙猫算法求解化工动态优化问题

Hybrid sand cat algorithm for solving dynamic optimization problems in chemical engineering

化工动态优化问题的求解是实现化工过程自动控制的基础,对环保与经济效益方面均有理论和实际意义。提出一种ISCSO(混合策略的沙猫优化算法)来达到反应器高效优化的目的。首先,针对SCSO(沙猫算法)种群初始化缺乏多样性、容易聚集的问题,引入Circle混沌映射初始化种群,提高多样性。其次,针对沙猫算法在迭代后期收敛速度较慢、容易陷入局部最优的问题,引入随机游走策略。同时,采用柯西变异策略扰动全局最优解,生成新解,避免陷入局部最优,增强局部搜索能力。最后将其应用于3个具有挑战性的化学动态优化工程问题上,并与其他方法进行对比分析。结果表明,改进后的算法具有更强的寻优和求解能力,证明了其有效性和优越性。

The solution of chemical dynamic optimization problems is the basis for realizing the automatic control of chemical processes,which has both theoretical and practical significance for environmental protection and economic benefits.A mixed-strategy sand cat optimization algorithm was proposed to achieve efficient optimization of the reactor.First,for the problem that the population initialization of sand cat algorithm lacked diversity and was easy to aggregate,Circle chaotic mapping was introduced to initialize the population,which improved the diversity.Second,for the problem that the sand cat algorithm converged slowly in the late iteration and was easy to fall into the local optimum,a stochastic wandering strategy was introduced.At the same time,the Cauchy variation strategy was used to perturb the global optimal solution and generated a new solution to avoid falling into the local optimum and enhanced the local search capability.Finally,it was applied to three challenging chemical dynamic optimization engineering problems and analyzed in comparison with other methods.The results show that the improved algorithm has stronger optimization and solution capabilities,proving its effectiveness and superiority.