چکیده مقاله
Most optimization problems in water resources management require tradeoffs between conflicting objectives Multi objective optimization is a growing research area with the aim of finding the Pareto optimal set of solutions which defines the optimal trade offs In past studies, the focus has been on developing methods to find Pareto fronts with better diversity and coverage the issue of objective function evaluation was of secondary importance However, in water resource applications, objective function evaluations can be computationally very expensive This leads to our motivation of developing a multi objective optimization method which not only converges to the optimal Pareto front with improved diversity but also with fewer function evaluations An efficient multiobjective ant colony optimization method EMOACO is proposed and compared against benchmark methods such as NSGA II, eMOEA and SMPSO The results demonstrated the capability of EMOACO to converge to the approximate Pareto optimal with significantly fewer evaluations
کلیدواژهها
نویسندگان
MOHAMMAD MORTAZAVI
School of Engineering, The University of Newcastle, Newcastle, NSW ۲۳۰۸, Australia
GEORGE KUCZERA
MOHAMMAD MORTAZAVI School of Engineering, The University of Newcastle, Newcastle, NSW ۲۳۰۸, AustraliaLIJIE CUI
LIJIE CUI
MOHAMMAD MORTAZAVI School of Engineering, The University of Newcastle, Newcastle, NSW ۲۳۰۸, AustraliaGEORGE KUCZERA
شیوه ارجاع
MORTAZAVI, MOHAMMAD and KUCZERA, GEORGE and CUI, LIJIE,1391,Efficient Multi-Objective Ant Colony Optimization,9th International Congress on Civil Engineering,Isfahan
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