In the paper, a fuzzy multi-objective Particle Swarm Optimization (MOPSO) hybrid algorithm applying to ethene cracking process was investigated. Pareto dominance and fuzzy decision.making were incorporated into panicle swarm optimization. Our algorithm took operation condition as repository of particles that was later used by other particles to guide their own flight. The optimum operation condition of every objective was incorperated into solution. Based on sort order, the scope and qulity of Pareto solution was extended. Satisfactory solution was get from Parcto set through fuzzy evaluate. The optimum operation condition was deduced.%文中研究了模糊多目标粒子群算法(MOPSO)在乙烯裂解工业中应用.算法在Pareto排序基础上引入子目标的最优操作条件来扩展属于非劣解集的操作条件范围,使非劣解集对于每个单目标而言都有较广的覆盖范围,确保非劣解集(操作条件)均匀分布,改进了非劣解集的质量,同时对非劣解引入工况实际要求,通过后验的模糊评价,来确定非劣解的满意操作条件,为决策者提供了明确的操作条件.将模糊多目标粒子群算法用于解决乙烯裂解过程中乙烯和丙烯收率多目标优化问题,较好地平衡了两种目标之间的冲突,为流程工业多目标优化问题提供了理论指导.
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