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...
Saved in:
| Published in: | Annals of operations research Vol. 292; no. 2; pp. 605 - 625 |
|---|---|
| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
Springer US
01.09.2020
Springer Springer Nature B.V |
| Subjects: | |
| ISSN: | 0254-5330, 1572-9338 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|---|
| Bibliography: | 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 |