The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Ola Svensson - One of the best experts on this subject based on the ideXlab platform.
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on bounded pitch inequalities for the min knapsack polytope
Lecture Notes in Computer Science, 2018Co-Authors: Yuri Faenza, Igor Malinovic, Monaldo Mastrolilli, Ola SvenssonAbstract:In the min-knapsack problem one aims at choosing a set of objects with minimum total cost and total profit above a given threshold. In this paper, we study a class of valid inequalities for min-knapsack known as bounded pitch inequalities, which generalize the well-known unweighted cover inequalities. While separating over pitch-1 inequalities is NP-Hard, we show that approximate separation over the set of pitch-1 and pitch-2 inequalities can be done in polynomial time. We also investigate integrality gaps of linear relaxations for min-knapsack when these inequalities are added. Among other results, we show that, for any fixed t, the t-th CG closure of the natural linear relaxation has the unbounded integrality gap.
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no small linear program approximates vertex cover within a factor 2 e
Foundations of Computer Science, 2015Co-Authors: Abbas Bazzi, Samuel Fiorini, Sebastian Pokutta, Ola SvenssonAbstract:The vertex cover problem is one of the most important and intensively studied combinatorial optimization problems. Khot and Regevproved that the problem is NP-hard to approximate within a factor2 - a#x03B5;, assuming the Unique Games Conjecture (UGC). This is tight because the problem has an easy 2-approximation algorithm. Without resorting to the UGC, the best in approximability result for the problem is due to Dinur and Safra: vertex cover is NP-hard to approximate within a factor 1.3606. We prove the following unconditional result about linear programming (LP)relaxations of the problem: every LP relaxation that approximates vertex cover within a factor of 2-a#x03B5; has super-polynomially many inequalities. As a direct consequence of our methods, we also establish that LP relaxations (as well as SDP relaxations) that approximate the independent set problem within any constant factor have super-polynomially many inequalities.
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no small linear program approximates vertex cover within a factor 2 epsilon
arXiv: Computational Complexity, 2015Co-Authors: Abbas Bazzi, Samuel Fiorini, Sebastian Pokutta, Ola SvenssonAbstract:The vertex cover problem is one of the most important and intensively studied combinatorial optimization problems. Khot and Regev (2003) proved that the problem is NP-hard to approximate within a factor $2 - \epsilon$, assuming the Unique Games Conjecture (UGC). This is tight because the problem has an easy 2-approximation algorithm. Without resorting to the UGC, the best inapproximability result for the problem is due to Dinur and Safra (2002): vertex cover is NP-hard to approximate within a factor 1.3606. We prove the following unconditional result about linear programming (LP) relaxations of the problem: every LP relaxation that approximates vertex cover within a factor $2-\epsilon$ has super-polynomially many inequalities. As a direct consequence of our methods, we also establish that LP relaxations (as well as SDP relaxations) that approximate the independent set problem within any constant factor have super-polynomial size.
Jungahn Kim - One of the best experts on this subject based on the ideXlab platform.
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miscibility of syndiotactic polystyrene atactic polystyrene blends by crystallization kinetics and enthalpy relaxation
Polymer, 1998Co-Authors: Bo Ki Hong, Jungahn KimAbstract:Abstract The miscibility of syndiotactic polystyrene (sPS)/atactic polystyrene (aPS) blends, whose constituent polymers have close T g s was investigated by crystallization kinetics and enthalpy relaxation. It was observed from crystallization kinetics experiment that both the spherulite growth rate and the overall crystallization rate of sPS in blends decrease with an increasing amount of aPS, indicating that sPS is diluted with aPS. When enthalpy relaxations of the blends are examined, it is revealed that the enthalpy recovery of sPS/aPS blends shows a single peak whose relaxation time is intermediate between those of sPS and aPS, and that the relaxation time of the blends gradually increases with the amount of aPS. From these results, it is concluded that sPS/aPS blends are completely miscible over the entire composition.
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Miscibility of syndiotactic polystyrene/atactic polystyrene blends by crystallization kinetics and enthalpy relaxation
Polymer, 1998Co-Authors: Bo Ki Hong, Jungahn KimAbstract:Abstract The miscibility of syndiotactic polystyrene (sPS)/atactic polystyrene (aPS) blends, whose constituent polymers have close T g s was investigated by crystallization kinetics and enthalpy relaxation. It was observed from crystallization kinetics experiment that both the spherulite growth rate and the overall crystallization rate of sPS in blends decrease with an increasing amount of aPS, indicating that sPS is diluted with aPS. When enthalpy relaxations of the blends are examined, it is revealed that the enthalpy recovery of sPS/aPS blends shows a single peak whose relaxation time is intermediate between those of sPS and aPS, and that the relaxation time of the blends gradually increases with the amount of aPS. From these results, it is concluded that sPS/aPS blends are completely miscible over the entire composition.
Abbas Bazzi - One of the best experts on this subject based on the ideXlab platform.
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no small linear program approximates vertex cover within a factor 2 e
Foundations of Computer Science, 2015Co-Authors: Abbas Bazzi, Samuel Fiorini, Sebastian Pokutta, Ola SvenssonAbstract:The vertex cover problem is one of the most important and intensively studied combinatorial optimization problems. Khot and Regevproved that the problem is NP-hard to approximate within a factor2 - a#x03B5;, assuming the Unique Games Conjecture (UGC). This is tight because the problem has an easy 2-approximation algorithm. Without resorting to the UGC, the best in approximability result for the problem is due to Dinur and Safra: vertex cover is NP-hard to approximate within a factor 1.3606. We prove the following unconditional result about linear programming (LP)relaxations of the problem: every LP relaxation that approximates vertex cover within a factor of 2-a#x03B5; has super-polynomially many inequalities. As a direct consequence of our methods, we also establish that LP relaxations (as well as SDP relaxations) that approximate the independent set problem within any constant factor have super-polynomially many inequalities.
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no small linear program approximates vertex cover within a factor 2 epsilon
arXiv: Computational Complexity, 2015Co-Authors: Abbas Bazzi, Samuel Fiorini, Sebastian Pokutta, Ola SvenssonAbstract:The vertex cover problem is one of the most important and intensively studied combinatorial optimization problems. Khot and Regev (2003) proved that the problem is NP-hard to approximate within a factor $2 - \epsilon$, assuming the Unique Games Conjecture (UGC). This is tight because the problem has an easy 2-approximation algorithm. Without resorting to the UGC, the best inapproximability result for the problem is due to Dinur and Safra (2002): vertex cover is NP-hard to approximate within a factor 1.3606. We prove the following unconditional result about linear programming (LP) relaxations of the problem: every LP relaxation that approximates vertex cover within a factor $2-\epsilon$ has super-polynomially many inequalities. As a direct consequence of our methods, we also establish that LP relaxations (as well as SDP relaxations) that approximate the independent set problem within any constant factor have super-polynomial size.
Bo Ki Hong - One of the best experts on this subject based on the ideXlab platform.
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miscibility of syndiotactic polystyrene atactic polystyrene blends by crystallization kinetics and enthalpy relaxation
Polymer, 1998Co-Authors: Bo Ki Hong, Jungahn KimAbstract:Abstract The miscibility of syndiotactic polystyrene (sPS)/atactic polystyrene (aPS) blends, whose constituent polymers have close T g s was investigated by crystallization kinetics and enthalpy relaxation. It was observed from crystallization kinetics experiment that both the spherulite growth rate and the overall crystallization rate of sPS in blends decrease with an increasing amount of aPS, indicating that sPS is diluted with aPS. When enthalpy relaxations of the blends are examined, it is revealed that the enthalpy recovery of sPS/aPS blends shows a single peak whose relaxation time is intermediate between those of sPS and aPS, and that the relaxation time of the blends gradually increases with the amount of aPS. From these results, it is concluded that sPS/aPS blends are completely miscible over the entire composition.
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Miscibility of syndiotactic polystyrene/atactic polystyrene blends by crystallization kinetics and enthalpy relaxation
Polymer, 1998Co-Authors: Bo Ki Hong, Jungahn KimAbstract:Abstract The miscibility of syndiotactic polystyrene (sPS)/atactic polystyrene (aPS) blends, whose constituent polymers have close T g s was investigated by crystallization kinetics and enthalpy relaxation. It was observed from crystallization kinetics experiment that both the spherulite growth rate and the overall crystallization rate of sPS in blends decrease with an increasing amount of aPS, indicating that sPS is diluted with aPS. When enthalpy relaxations of the blends are examined, it is revealed that the enthalpy recovery of sPS/aPS blends shows a single peak whose relaxation time is intermediate between those of sPS and aPS, and that the relaxation time of the blends gradually increases with the amount of aPS. From these results, it is concluded that sPS/aPS blends are completely miscible over the entire composition.
Samuel Fiorini - One of the best experts on this subject based on the ideXlab platform.
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no small linear program approximates vertex cover within a factor 2 e
Foundations of Computer Science, 2015Co-Authors: Abbas Bazzi, Samuel Fiorini, Sebastian Pokutta, Ola SvenssonAbstract:The vertex cover problem is one of the most important and intensively studied combinatorial optimization problems. Khot and Regevproved that the problem is NP-hard to approximate within a factor2 - a#x03B5;, assuming the Unique Games Conjecture (UGC). This is tight because the problem has an easy 2-approximation algorithm. Without resorting to the UGC, the best in approximability result for the problem is due to Dinur and Safra: vertex cover is NP-hard to approximate within a factor 1.3606. We prove the following unconditional result about linear programming (LP)relaxations of the problem: every LP relaxation that approximates vertex cover within a factor of 2-a#x03B5; has super-polynomially many inequalities. As a direct consequence of our methods, we also establish that LP relaxations (as well as SDP relaxations) that approximate the independent set problem within any constant factor have super-polynomially many inequalities.
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no small linear program approximates vertex cover within a factor 2 epsilon
arXiv: Computational Complexity, 2015Co-Authors: Abbas Bazzi, Samuel Fiorini, Sebastian Pokutta, Ola SvenssonAbstract:The vertex cover problem is one of the most important and intensively studied combinatorial optimization problems. Khot and Regev (2003) proved that the problem is NP-hard to approximate within a factor $2 - \epsilon$, assuming the Unique Games Conjecture (UGC). This is tight because the problem has an easy 2-approximation algorithm. Without resorting to the UGC, the best inapproximability result for the problem is due to Dinur and Safra (2002): vertex cover is NP-hard to approximate within a factor 1.3606. We prove the following unconditional result about linear programming (LP) relaxations of the problem: every LP relaxation that approximates vertex cover within a factor $2-\epsilon$ has super-polynomially many inequalities. As a direct consequence of our methods, we also establish that LP relaxations (as well as SDP relaxations) that approximate the independent set problem within any constant factor have super-polynomial size.
