DocumentCode :
3743668
Title :
Bounding the greedy strategy in finite-horizon string optimization
Author :
Yajing Liu;Edwin K. P. Chong;Ali Pezeshki
Author_Institution :
Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, 80523, USA
fYear :
2015
Firstpage :
3900
Lastpage :
3905
Abstract :
We consider an optimization problem where the decision variable is a string of bounded length. For some time there has been an interest in bounding the performance of the greedy strategy for this problem. Here, we provide weakened sufficient conditions for the greedy strategy to be bounded by a factor of (1 - (1 - 1/K)K), where K is the optimization horizon length. Specifically, we introduce the notions of K-submodularity and K-GO-concavity, which together are sufficient for this bound to hold. By introducing a notion of curvature η ∈ (0; 1), we prove an even tighter bound with the factor (1/η)(1-e). Finally, we illustrate the strength of our results by considering two example applications. We show that our results provide weaker conditions on parameter values in these applications than in previous results.
Keywords :
"Linear programming","Optimization","Yttrium","Computers","Conferences","Decision making","Economics"
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2015 IEEE 54th Annual Conference on
Type :
conf
DOI :
10.1109/CDC.2015.7402826
Filename :
7402826
Link To Document :
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