Bounds in multi-horizon stochastic programs

In this paper, we present bounds for multi-horizon stochastic optimization problems , a class of problems introduced in Kaut et al. (Comput Manag Sci 11:179–193, 2014 ) relevant in many industry-life applications typically involving strategic and operational decisions on two different time scales. A...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Annals of operations research Ročník 292; číslo 2; s. 605 - 625
Hlavní autoři: Maggioni, Francesca, Allevi, Elisabetta, Tomasgard, Asgeir
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.09.2020
Springer
Springer Nature B.V
Témata:
Alternative energy sources
Approximation
Business and Management
Combinatorics
Energy industry
Expected values
Formulations
Infrastructure
Mathematical optimization
Meat industry
Operations research
Operations Research/Decision Theory
Optimization
Production management
Random variables
S.I.: Stochastic Optimization: Theory & Applications in Memory of M.Bertocchi
Stochastic programming
Theory of Computation
Trees
Italy
Stochastic programs
Operational decisions
Multi-horizon
Energy
Bounds
Strategic decisions
ISSN:0254-5330, 1572-9338
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In this paper, we present bounds for multi-horizon stochastic optimization problems , a class of problems introduced in Kaut et al. (Comput Manag Sci 11:179–193, 2014 ) relevant in many industry-life applications typically involving strategic and operational decisions on two different time scales. After providing three general mathematical formulations of a multi-horizon stochastic program, we extend the definition of the traditional Expected Value problem and Wait-and-See problem from stochastic programming in a multi-horizon framework. New measures are introduced allowing to quantify the importance of the uncertainty at both strategic and operational levels. Relations among the solution approaches are then determined and chain of inequalities provided. Numerical experiments based on an energy planning application are finally presented.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-019-03244-9