Paper Info
Title
On approximation of the best case optimal value in interval linear programming.
Abstract
Interval linear programming addresses problems with uncertain coefficients and the only information that we have is that the true values lie somewhere in the prescribed intervals. For the inequality constraint problem, computing the worst case scenario and the corresponding optimal value is an easy task, but the best case optimal value calculation is known to be NP-hard. In this paper, we discuss lower and upper bound approximation for the best case optimal value, and propose suitable methods for both of them. We also propose a not apriori exponential algorithm for computing the best case optimal value. The presented techniques are tested by randomly generated data, and also applied in a simple data classification problem.
Year
DOI
Venue
2014
10.1007/s11590-013-0715-5
Optimization Letters
Keywords
Field
DocType
Linear programming, Interval linear systems, Interval analysis
Mathematical optimization,Exponential function,Interval linear programming,Upper and lower bounds,A priori and a posteriori,Linear programming,Data classification,Worst-case scenario,Interval arithmetic,Mathematics
Journal
Volume
Issue
ISSN
8
7
1862-4480
Citations 
PageRank 
References 
12
0.67
7
Authors
1
Name
Order
Citations
PageRank
Milan Hladík126836.33