Fine-tuned robust optimization: Attaining robustness and targeting ideality-Reference-Cited by-同舟云学术

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Fine-tuned robust optimization: Attaining robustness and targeting ideality

Published:2022-03 Issue: Volume:165 Page:107890
ISSN:0360-8352
Container-title:Computers & Industrial Engineering
language:en
Short-container-title:Computers & Industrial Engineering

Author:

Cesar Balbino Barbosa Filho Alexandre,Mauro da Silva Neiro Sergio

Funder

National Council for Scientific and Technological Development

Publisher

Elsevier BV

Subject

General Engineering,General Computer Science

Reference56 articles.

1. Min–max and min–max regret versions of combinatorial optimization problems: A survey;Aissi;European Journal of Operational Research,2009

2. A new robust optimization approach for integrated multi-echelon, multi-product, multi-period supply chain network design under process uncertainty;Akbari;The International Journal of Advanced Manufacturing Technology,2015

3. Scenario relaxation algorithm for finite scenario-based min–max regret and min–max relative regret robust optimization;Assavapokee;Computers & Operations Research,2008

4. Robust optimization model and algorithm for logistics center location and allocation under uncertain environment;Baohua;Journal of Transportation Systems Engineering and Information Technology,2009

5. Robust convex optimization;Ben-Tal;Mathematics of Operations Research,1998

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1. Stochastic portfolio optimization: A regret-based approach on volatility risk measures: An empirical evidence from The New York stock market;PLOS ONE;2024-04-22

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