This paper formalizes and adapts the well known concept of Pareto efficiency in the context of the popular robust optimization (RO) methodology. We argue that the classical RO paradigm need not produce solutions that possess the associated property of Pareto optimality, and illustrate via examples ho...
Iancu, D., Trichakis, N.: Pareto efficiency in robust optimization. Management Science 60, 130-147 (2014)D. A. Iancu and N. Trichakis. Pareto efficiency in robust optimization. Management Science, 60(1): 130-147, 2014.D. A. Iancu and N. Trichakis, "Pareto efficiency in robust ...
Pareto optimality analysis between energy efficiency and protein cost reveals that the naturally evolved ED and EMP pathways are indeed among the most protein cost-efficient pathways in their respective ATP yield categories and remain thermodynamically feasible across a wide range of ATP/ADP ratios and...
We compute the spectral-energy efficiency Pareto front in Poisson cellular networks, by formulating a spectral-energy efficiency bi-objective optimization problem as a function of either the transmit power or the density of the base stations. Capitalizing on fundamental theoretical results on weighted Tc...
In47,48, the authors have proposed novel approaches in multi-objective optimization and algorithm efficiency within machine learning environments. For online sequential learning machines, in47 a multi-objective model selection approach is suggested to enhance the target output error, control quality, and...
efficiency.EspeciallywithrespecttotheconstantevolutionThedesignoftheinductoristhefoundationfordesigning ofemerging,arobustoptimizationaPFCrectifier.Anyproposeddesignmodelhastodealwith methodologycanprovideanefficientpre-sizingtoolformaiccoresandwindingwirestogetaproperdesign.In ...
However, they exhibit problems of efficiency, such as slow convergence to the optimal front and low performance on the problems with many objectives. Li et al. (2016) propose a bi-criterion evolution framework of Pareto and non-Pareto criteria to apply it in the evolutionary algorithms to ...
Specifically, the new approach uses the efficiency and effectiveness of optimization to rapidly compare numerous designs, and characterize the tradeoff properties within the multiobjective design space. As such, the new approach differs significantly from traditional (non-optimization based) concept ...
One test function and an (s, S) inventory system experiment illustrate the potential and efficiency of the proposed sequential optimization algorithm for constrained multi-objective optimization problems in stochastic simulation, which is especially useful in Operations Research and Management Science....
In addition to the improvement in evolution efficiency, the Pareto front perspective allows the user to choose appropriate models for further analysis or deployment. The Pareto front avoids the need to a priori specify a trade-off between competing objectives (e.g. complexity and performance) by ...