Integer Programming Reformulations in Interval Linear Programming
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10437050" target="_blank" >RIV/00216208:11320/21:10437050 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.1007/978-3-030-86841-3_1" target="_blank" >https://doi.org/10.1007/978-3-030-86841-3_1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-86841-3_1" target="_blank" >10.1007/978-3-030-86841-3_1</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Integer Programming Reformulations in Interval Linear Programming
Popis výsledku v původním jazyce
Interval linear programming provides a mathematical model for optimization problems affected by uncertainty, in which the uncertain data can be independently perturbed within the given lower and upper bounds. Many tasks in interval linear programming, such as describing the feasible set or computing the range of optimal values, can be solved by the orthant decomposition method, which reduces the interval problem to a set of linear-programming subproblems-one linear program over each orthant of the solution space. In this paper, we explore the possibility of utilizing the existing integer programming techniques in tackling some of these difficult problems by deriving a mixed-integer linear programming reformulation. Namely, we focus on the optimal value range problem, which is NP-hard for general interval linear programs. For this problem, we compare the obtained reformulation with the traditionally used orthant decomposition and also with the non-linear absolute-value formulation that serves as a basis for both of the former approaches. (C) 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Název v anglickém jazyce
Integer Programming Reformulations in Interval Linear Programming
Popis výsledku anglicky
Interval linear programming provides a mathematical model for optimization problems affected by uncertainty, in which the uncertain data can be independently perturbed within the given lower and upper bounds. Many tasks in interval linear programming, such as describing the feasible set or computing the range of optimal values, can be solved by the orthant decomposition method, which reduces the interval problem to a set of linear-programming subproblems-one linear program over each orthant of the solution space. In this paper, we explore the possibility of utilizing the existing integer programming techniques in tackling some of these difficult problems by deriving a mixed-integer linear programming reformulation. Namely, we focus on the optimal value range problem, which is NP-hard for general interval linear programs. For this problem, we compare the obtained reformulation with the traditionally used orthant decomposition and also with the non-linear absolute-value formulation that serves as a basis for both of the former approaches. (C) 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Klasifikace
Druh
C - Kapitola v odborné knize
CEP obor
—
OECD FORD obor
50201 - Economic Theory
Návaznosti výsledku
Projekt
<a href="/cs/project/GA18-04735S" target="_blank" >GA18-04735S: Nové přístupy pro relaxační a aproximační techniky v deterministické globální optimalizaci</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2021
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název knihy nebo sborníku
AIRO Springer Series
ISBN
978-3-030-86841-3
Počet stran výsledku
11
Strana od-do
3-13
Počet stran knihy
247
Název nakladatele
Springer Nature
Místo vydání
Cham
Kód UT WoS kapitoly
—