401 research outputs found
Optimization of the structural and control system for LSS with reduced-order model
The objective is the simultaneous design of the structural and control system for space structures. The minimum weight of the structure is the objective function, and the constraints are placed on the closed loop distribution of the frequencies and the damping parameters. The controls approach used is linear quadratic regulator with constant feedback. A reduced-order control system is used. The effect of uncontrolled modes is taken into consideration by the model error sensitivity suppression (MESS) technique which modified the weighting parameters for the control forces. For illustration, an ACOSS-FOUR structure is designed for a different number of controlled modes with specified values for the closed loop damping parameters and frequencies. The dynamic response of the optimum designs for an initial disturbance is compared
Structural Optimization Using the Newton Modified Barrier Method
The Newton Modified Barrier Method (NMBM) is applied to structural optimization problems with large a number of design variables and constraints. This nonlinear mathematical programming algorithm was based on the Modified Barrier Function (MBF) theory and the Newton method for unconstrained optimization. The distinctive feature of the NMBM method is the rate of convergence that is due to the fact that the design remains in the Newton area after each Lagrange multiplier update. This convergence characteristic is illustrated by application to structural problems with a varying number of design variables and constraints. The results are compared with those obtained by optimality criteria (OC) methods and by the ASTROS program
Covering problems in edge- and node-weighted graphs
This paper discusses the graph covering problem in which a set of edges in an
edge- and node-weighted graph is chosen to satisfy some covering constraints
while minimizing the sum of the weights. In this problem, because of the large
integrality gap of a natural linear programming (LP) relaxation, LP rounding
algorithms based on the relaxation yield poor performance. Here we propose a
stronger LP relaxation for the graph covering problem. The proposed relaxation
is applied to designing primal-dual algorithms for two fundamental graph
covering problems: the prize-collecting edge dominating set problem and the
multicut problem in trees. Our algorithms are an exact polynomial-time
algorithm for the former problem, and a 2-approximation algorithm for the
latter problem, respectively. These results match the currently known best
results for purely edge-weighted graphs.Comment: To appear in SWAT 201
Near-optimal asymmetric binary matrix partitions
We study the asymmetric binary matrix partition problem that was recently
introduced by Alon et al. (WINE 2013) to model the impact of asymmetric
information on the revenue of the seller in take-it-or-leave-it sales.
Instances of the problem consist of an binary matrix and a
probability distribution over its columns. A partition scheme
consists of a partition for each row of . The partition acts
as a smoothing operator on row that distributes the expected value of each
partition subset proportionally to all its entries. Given a scheme that
induces a smooth matrix , the partition value is the expected maximum
column entry of . The objective is to find a partition scheme such that
the resulting partition value is maximized. We present a -approximation
algorithm for the case where the probability distribution is uniform and a
-approximation algorithm for non-uniform distributions, significantly
improving results of Alon et al. Although our first algorithm is combinatorial
(and very simple), the analysis is based on linear programming and duality
arguments. In our second result we exploit a nice relation of the problem to
submodular welfare maximization.Comment: 17 page
A note on anti-coordination and social interactions
This note confirms a conjecture of [Bramoull\'{e}, Anti-coordination and
social interactions, Games and Economic Behavior, 58, 2007: 30-49]. The
problem, which we name the maximum independent cut problem, is a restricted
version of the MAX-CUT problem, requiring one side of the cut to be an
independent set. We show that the maximum independent cut problem does not
admit any polynomial time algorithm with approximation ratio better than
, where is the number of nodes, and arbitrarily
small, unless P=NP. For the rather special case where each node has a degree of
at most four, the problem is still MAXSNP-hard.Comment: 7 page
Fixed-parameter tractability of multicut parameterized by the size of the cutset
Given an undirected graph , a collection of
pairs of vertices, and an integer , the Edge Multicut problem ask if there
is a set of at most edges such that the removal of disconnects
every from the corresponding . Vertex Multicut is the analogous
problem where is a set of at most vertices. Our main result is that
both problems can be solved in time , i.e.,
fixed-parameter tractable parameterized by the size of the cutset in the
solution. By contrast, it is unlikely that an algorithm with running time of
the form exists for the directed version of the problem, as
we show it to be W[1]-hard parameterized by the size of the cutset
Fast Distributed Approximation for Max-Cut
Finding a maximum cut is a fundamental task in many computational settings.
Surprisingly, it has been insufficiently studied in the classic distributed
settings, where vertices communicate by synchronously sending messages to their
neighbors according to the underlying graph, known as the or
models. We amend this by obtaining almost optimal
algorithms for Max-Cut on a wide class of graphs in these models. In
particular, for any , we develop randomized approximation
algorithms achieving a ratio of to the optimum for Max-Cut on
bipartite graphs in the model, and on general graphs in the
model.
We further present efficient deterministic algorithms, including a
-approximation for Max-Dicut in our models, thus improving the best known
(randomized) ratio of . Our algorithms make non-trivial use of the greedy
approach of Buchbinder et al. (SIAM Journal on Computing, 2015) for maximizing
an unconstrained (non-monotone) submodular function, which may be of
independent interest
Reexamination of a multisetting Bell inequality for qudits
The class of d-setting, d-outcome Bell inequalities proposed by Ji and
collaborators [Phys. Rev. A 78, 052103] are reexamined. For every positive
integer d > 2, we show that the corresponding non-trivial Bell inequality for
probabilities provides the maximum classical winning probability of the
Clauser-Horne-Shimony-Holt-like game with d inputs and d outputs. We also
demonstrate that the general classical upper bounds given by Ji et al. are
underestimated, which invalidates many of the corresponding correlation
inequalities presented thereof. We remedy this problem, partially, by providing
the actual classical upper bound for d less than or equal to 13 (including
non-prime values of d). We further determine that for prime value d in this
range, most of these probability and correlation inequalities are tight, i.e.,
facet-inducing for the respective classical correlation polytope. Stronger
lower and upper bounds on the quantum violation of these inequalities are
obtained. In particular, we prove that once the probability inequalities are
given, their correlation counterparts given by Ji and co-workers are no longer
relevant in terms of detecting the entanglement of a quantum state.Comment: v3: Published version (minor rewordings, typos corrected, upper
bounds in Table III improved/corrected); v2: 7 pages, 1 figure, 4 tables
(substantially revised with new results on the tightness of the correlation
inequalities included); v1: 7.5 pages, 1 figure, 4 tables (Comments are
welcome
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