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Comprehensive optimization of batch process based on particle swarm optimization algorithm

机译：基于粒子群算法的批处理过程综合优化

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Based on Iterative Particle Swarm Optimization (PSO) Algorithm, comprehensive optimization problem of batch process is discussed in this paper. Batch process optimization problems in general to product concentration as optimization goal, if optimization object is changed to the sum of the product concentration, the reciprocal of reaction time and the reciprocal of energy loss and then optimization method will be more complex. Based on the iterative particle swarm optimization algorithm, optimal solution is obtained by searching for optimal trajectory. Results of study are applied to classical chemical reaction cases. Simulation results show that this algorithm is better than single objective algorithm in speed of optimization and efficient use of energy.
机译：基于迭代粒子群优化算法，讨论了批处理过程的综合优化问题。批处理过程中的优化问题一般以产品浓度为优化目标，如果将优化对象更改为产品浓度之和，反应时间的倒数和能量损失的倒数，那么优化方法将更加复杂。基于迭代粒子群优化算法，通过搜索最优轨迹获得最优解。研究结果适用于经典的化学反应案例。仿真结果表明，该算法在优化速度和有效利用能量方面均优于单目标算法。

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