Mixed-Integer Nonlinear Programming Optimization Strategies for Batch Plant Design Problems

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• 作者：Antonin Ponsich ; Catherine Azzaro-Pantel ; Serge Domenech ; Luc Pibouleau
• 刊名：Industrial & Engineering Chemistry Research
• 出版年：2007
• 出版时间：January 31, 2007
• 年：2007
• 卷：46
• 期：3
• 页码：854 - 863
• 全文大小：251K
• 年卷期：v.46,no.3(January 31, 2007)
• ISSN：1520-5045

文摘

Due to their large variety of applications, complex optimization problems induced a great effort to developefficient solution techniques, dealing with both continuous and discrete variables involved in nonlinear functions.But among the diversity of those optimization methods, the choice of the relevant technique for the treatmentof a given problem keeps being a thorny issue. Within the process engineering context, batch plant designproblems provide a good framework to test the performances of various optimization methods: on the onehand, two mathematical programming techniques-DICOPT++ and SBB, implemented in the GAMSenvironment-and on the other hand, one stochastic method, i.e., a genetic algorithm. Seven examples, showingan increasing complexity, were solved with these three techniques. The resulting comparison enables theevaluation of their efficiency in order to highlight the most appropriate method for a given problem instance.It was proved that the best performing method is SBB, even if the genetic algorithm (GA) also providesinteresting solutions, in terms of quality as well as of computational time.