Optimal computing budget allocation for complete ranking with input uncertainty-Reference-Cited by-同舟云学术

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Optimal computing budget allocation for complete ranking with input uncertainty

Published:2019-10-14 Issue:5 Volume:52 Page:489-499
ISSN:2472-5854
Container-title:IISE Transactions
language:en
Short-container-title:IISE Transactions

Author:

Xiao Hui¹,Gao Fei²,Lee Loo Hay³

Affiliation:

1. Department of Management Science and Engineering, School of Statistics, Southwestern University of Finance and Economics, Chengdu, China;

2. Department of Systems Engineering and Engineering Management, City University of Hong Kong, Kowloon, Hong Kong;

3. Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/24725854.2019.1659524

Reference39 articles.

1. Scenario relaxation algorithm for finite scenario-based min–max regret and min–max relative regret robust optimization

2. Complete statistical ranking of populations, with tables and applications

3. A Comparison of Selection Schemes Used in Evolutionary Algorithms

4. Selecting a Selection Procedure

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1. Optimal computing budget allocation for selecting the optimal subset of multi-objective simulation optimization problems;Automatica;2024-11

2. Optimal Computing Budget Allocation for Data-Driven Ranking and Selection;INFORMS Journal on Optimization;2024-09-04

3. Bayesian Stochastic Gradient Descent for Stochastic Optimization with Streaming Input Data;SIAM Journal on Optimization;2024-01-25

4. Ranking and Selection with Two-Stage Decision;SSRN Electronic Journal;2024

5. Data-Driven Optimal Allocation for Ranking and Selection under Unknown Sampling Distributions;2023 Winter Simulation Conference (WSC);2023-12-10

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