Min–max and min–max regret versions of combinatorial optimization problems: A survey

Min–max and min–max regret criteria are commonly used to define robust solutions. After motivating the use of these criteria, we present general results. Then, we survey complexity results for the min–max and min–max regret versions of some combinatorial optimization problems: shortest path, spannin...

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Vydáno v:European journal of operational research Ročník 197; číslo 2; s. 427 - 438
Hlavní autoři: Aissi, Hassene, Bazgan, Cristina, Vanderpooten, Daniel
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 01.09.2009
Elsevier
Elsevier Sequoia S.A
Edice:European Journal of Operational Research
Témata:
ISSN:0377-2217, 1872-6860
On-line přístup:Získat plný text
Tagy: Přidat tag
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Abstract Min–max and min–max regret criteria are commonly used to define robust solutions. After motivating the use of these criteria, we present general results. Then, we survey complexity results for the min–max and min–max regret versions of some combinatorial optimization problems: shortest path, spanning tree, assignment, min cut, min s– t cut, knapsack. Since most of these problems are NP-hard, we also investigate the approximability of these problems. Furthermore, we present algorithms to solve these problems to optimality.
AbstractList Min–max and min–max regret criteria are commonly used to define robust solutions. After motivating the use of these criteria, we present general results. Then, we survey complexity results for the min–max and min–max regret versions of some combinatorial optimization problems: shortest path, spanning tree, assignment, min cut, min s– t cut, knapsack. Since most of these problems are NP-hard, we also investigate the approximability of these problems. Furthermore, we present algorithms to solve these problems to optimality.
Min-max and min-max regret criteria are commonly used to define robust solutions. After motivating the use of these criteria, we present general results. Then, we survey complexity results for the min-max and min-max regret versions of some combinatorial optimization problems: shortest path, spanning tree, assignment, min cut, min s-t cut, knapsack. Since most of these problems are NP-hard, we also investigate the approximability of these problems. Furthermore, we present algorithms to solve these problems to optimality. [PUBLICATION ABSTRACT]
Min-max and min-max regret criteria are commonly used to define robust solutions. After motivating the use of these criteria, we present general results. Then, we survey complexity results for the min-max and min-max regret versions of some combinatorial optimization problems: shortest path, spanning tree, assignment, min cut, min s-t cut, knapsack. Since most of these problems are NP-hard, we also investigate the approximability of these problems. Furthermore, we present algorithms to solve these problems to optimality.
Author Bazgan, Cristina
Aissi, Hassene
Vanderpooten, Daniel
Author_xml – sequence: 1
  givenname: Hassene
  surname: Aissi
  fullname: Aissi, Hassene
  email: aissi@lamsade.dauphine.fr
– sequence: 2
  givenname: Cristina
  surname: Bazgan
  fullname: Bazgan, Cristina
  email: bazgan@lamsade.dauphine.fr
– sequence: 3
  givenname: Daniel
  surname: Vanderpooten
  fullname: Vanderpooten, Daniel
  email: vdp@lamsade.dauphine.fr
BackLink http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=21374323$$DView record in Pascal Francis
http://econpapers.repec.org/article/eeeejores/v_3a197_3ay_3a2009_3ai_3a2_3ap_3a427-438.htm$$DView record in RePEc
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10.1287/opre.35.1.70
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Issue 2
Keywords Robustness
Min–max
Min–max regret
Approximation
Combinatorial optimization
Complexity
Spanning tree
Minimax method
NP hard problem
Shortest path
Min-max
Knapsack problem
Min-max regret
Language English
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SSID ssj0001515
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Snippet Min–max and min–max regret criteria are commonly used to define robust solutions. After motivating the use of these criteria, we present general results. Then,...
Min-max and min-max regret criteria are commonly used to define robust solutions. After motivating the use of these criteria, we present general results. Then,...
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SubjectTerms Applied sciences
Approximation
Assignment problem
Combinatorial optimization
Complexity
Exact sciences and technology
Flows in networks. Combinatorial problems
Knapsack problem
Min-max Min-max regret Combinatorial optimization Complexity Approximation Robustness
Min–max
Min–max regret
Operational research and scientific management
Operational research. Management science
Optimization algorithms
Robustness
Shortest path algorithms
Studies
Title Min–max and min–max regret versions of combinatorial optimization problems: A survey
URI https://dx.doi.org/10.1016/j.ejor.2008.09.012
http://econpapers.repec.org/article/eeeejores/v_3a197_3ay_3a2009_3ai_3a2_3ap_3a427-438.htm
https://www.proquest.com/docview/204194547
Volume 197
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