Optimal Computing Budget Allocation to Select the Nondominated Systems—A Large Deviations Perspective

DOI10.1109/TAC.2017.2779603zbMath1423.90245OpenAlexW2773271314MaRDI QIDQ4682352

Loo Hay Lee, Ek Peng Chew, Juxin Li, Giulia Pedrielli, Weizhi Liu

Publication date: 18 September 2018

Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/tac.2017.2779603

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Large deviations (60F10) Statistical ranking and selection procedures (62F07) Resource and cost allocation (including fair division, apportionment, etc.) (91B32)

Related Items (5)

An efficient simulation procedure for the expected opportunity cost using metamodels ⋮ Biobjective Simulation Optimization on Integer Lattices Using the Epsilon-Constraint Method in a Retrospective Approximation Framework ⋮ Pareto set estimation with guaranteed probability of correct selection ⋮ Efficient estimation of a risk measure requiring two-stage simulation optimization ⋮ Optimal budget allocation policy for tabu search in stochastic simulation optimization

This page was built for publication: Optimal Computing Budget Allocation to Select the Nondominated Systems—A Large Deviations Perspective