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The present work studies a maximum multicommodity flow problem with local constrains, which not only enrich the content of the multicommodity flow problem, but also can be used to operate optimization ...
This class of problems includes the maximum generalized assignment problem (GAP) 1 and a distributed caching problem (DCP) described in this paper. Given a β-approximation algorithm for finding the ...
Very recently, a polynomial-time algorithm, called ByFindStar2d, achieving an optimal approximation ratio of O (n1/2) for MAX d-CLIQUE and MAX d-CLUB is designed for any odd d ≥ 3 in [4].
Learn what approximation algorithms are, how they work, and what are their benefits and drawbacks for solving hard problems in optimization, scheduling, and more.
Learn what approximation algorithms are, how they work, and what are some examples and challenges in computer engineering.
The partial linear approximation algorithm for computing the constrained maximum likelihood estimator ˆϕ of the model presented in subsection 4.1 stems from the cyclic algorithm of N’Guessan and ...
The travelling salesman problem (TSP) remains one of the most challenging NP‐hard problems in combinatorial optimisation, with significant implications for logistics, network design and route ...
In this talk, we will present efficient approximation algorithms with near-optimal guarantees for the (general) stochastic knapsack problem, the stochastic orienteering problem, and the multi-armed ...
Technical Terms NP-hard: A classification for problems for which no polynomial-time algorithm is known, implying that a solution may require non-polynomial resources in the worst case.
Understand how approximation algorithms compute solutions that are guaranteed to be within some constant factor of the optimal solution. Develop a basic understanding of how linear and integer ...
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