Application of Heuristic Optimization Techniques and Algorithm Tuning to Multilayered Sorptive Barrier Design

详细信息    查看全文

• 作者：L. Shawn Matott ; Shannon L. Bartelt-Hunt ; Alan J. Rabideau ; K. R. Fowler
• 刊名：Environmental Science & Technology
• 出版年：2006
• 出版时间：October 15, 2006
• 年：2006
• 卷：40
• 期：20
• 页码：6354 - 6360
• 全文大小：334K
• 年卷期：v.40,no.20(October 15, 2006)
• ISSN：1520-5851

文摘

Although heuristic optimization techniques are increasinglyapplied in environmental engineering applications,algorithm selection and configuration are often approachedin an ad hoc fashion. In this study, the design of amultilayer sorptive barrier system served as a benchmarkproblem for evaluating several algorithm-tuning procedures,as applied to three global optimization techniques (geneticalgorithms, simulated annealing, and particle swarmoptimization). Each design problem was configured as acombinatorial optimization in which sorptive materials wereselected for inclusion in a landfill liner to minimize thetransport of three common organic contaminants. Relativeto multilayer sorptive barrier design, study results indicate(i) the binary-coded genetic algorithm is highly efficient andrequires minimal tuning, (ii) constraint violations must becarefully integrated to avoid poor algorithm convergence,and (iii) search algorithm performance is stronglyinfluenced by the physical-chemical properties of theorganic contaminants of concern. More generally, theresults suggest that formal algorithm tuning, which hasnot been widely applied to environmental engineeringoptimization, can significantly improve algorithm performanceand provide insight into the physical processes thatcontrol environmental systems.