6533b86efe1ef96bd12cbd58

RESEARCH PRODUCT

Efficient evolutionary approach to approximate the Pareto-optimal set in multiobjective optimization, UPS-EMOA

T. AittokoskiKaisa Miettinen

subject

Set (abstract data type)Pareto optimalMathematical optimizationControl and OptimizationApplied MathematicsPopulation sizeNew populationMulti-objective optimizationSoftwareMathematicsMultiobjective optimization algorithm

description

Solving real-life engineering problems requires often multiobjective, global, and efficient (in terms of objective function evaluations) treatment. In this study, we consider problems of this type by discussing some drawbacks of the current methods and then introduce a new population-based multiobjective optimization algorithm UPS-EMOA which produces a dense (not limited to the population size) approximation of the Pareto-optimal set in a computationally effective manner.

yearjournalcountryeditionlanguage
2010-12-01Optimization Methods and Software
https://doi.org/10.1080/10556780903548265