Local Search Based Approximation Algorithms for Two-Stage Stochastic Location Problems

2017 ◽  
pp. 197-209
Author(s):  
Felix J. L. Willamowski ◽  
Andreas Bley
Keyword(s):  
Approximation Algorithms ◽  
Local Search ◽  
Location Problems ◽  
Two Stage ◽  
Stochastic Location

Local search approximation algorithms for the sum of squares facility location problems

2019 ◽  
Vol 74 (4) ◽  
pp. 909-932
Author(s):  
Dongmei Zhang ◽  
Dachuan Xu ◽  
Yishui Wang ◽  
Peng Zhang ◽  
Zhenning Zhang
Keyword(s):  
Approximation Algorithms ◽  
Local Search ◽  
Facility Location ◽  
Sum Of Squares ◽  
Location Problems ◽  
Facility Location Problems

scholarly journals Local Search Heuristics for k-Median and Facility Location Problems

2004 ◽  
Vol 33 (3) ◽  
pp. 544-562 ◽  
Author(s):  
Vijay Arya ◽  
Naveen Garg ◽  
Rohit Khandekar ◽  
Adam Meyerson ◽  
Kamesh Munagala ◽  
...  
Keyword(s):  
Local Search ◽  
Facility Location ◽  
Location Problems ◽  
Facility Location Problems ◽  
Local Search Heuristics ◽  
Search Heuristics

Two-stage submodular maximization problem beyond nonnegative and monotone

2021 ◽  
pp. 1-16
Author(s):  
Zhicheng Liu ◽  
Hong Chang ◽  
Ran Ma ◽  
Donglei Du ◽  
Xiaoyan Zhang
Keyword(s):  
Approximation Algorithms ◽  
Approximation Algorithm ◽  
Objective Function ◽  
Modular Function ◽  
Submodular Function ◽  
Maximization Problem ◽  
Cardinality Constraint ◽  
Two Stage ◽  
Time Efficiency ◽  
Submodular Maximization

Abstract We consider a two-stage submodular maximization problem subject to a cardinality constraint and k matroid constraints, where the objective function is the expected difference of a nonnegative monotone submodular function and a nonnegative monotone modular function. We give two bi-factor approximation algorithms for this problem. The first is a deterministic $\left( {{1 \over {k + 1}}\left( {1 - {1 \over {{e^{k + 1}}}}} \right),1} \right)$ -approximation algorithm, and the second is a randomized $\left( {{1 \over {k + 1}}\left( {1 - {1 \over {{e^{k + 1}}}}} \right) - \varepsilon ,1} \right)$ -approximation algorithm with improved time efficiency.

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