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Marius Costandin

Publications and source records attributed to Marius Costandin.

14 recordsLinked to original sources

Vertex Loci of Max-Indicator Polytopes and Vertex Retrieval in Ball Polyhedra

The so called "max-indicator polytopes" were introduced in \cite{mainB} as an intersection of half-spaces related to the problem of finding the farthest in an intersection of balls $\mathcal{Q}$, from a given target point $C_S$. It was shown that if the target point belongs to the convex hull of the balls centers, then a specific intersection of half-spaces forms a single real variable parameterized polytope family which is used to characterized the extreme points. This paper, under the assumptions that the intersecting balls centers lie on a sphere and all have equal radii with only one vertex $x$, of $\mathcal{Q}$, meeting $1_{n \times 1}\cdot x = 0$, we provide an efficient algorithm to retrieve that vertex. The main idea behind the result is that the max-indicator polytopes vertices, as the family parameter varies, slide on some lines, that we call vertex locii. These lines pass through the space origin and the vertices of $\mathcal{Q}$. Perturbing the target point $C_S$ up and down along the direction $1_{n\times 1}$ we are able to show that the intersection of two simetrically perturbed max-indicator polytopes is strictly included in the unperturbed polytope, with the only boundary common points being on the line connecting the origin with the vertex of $\mathcal{Q}$ meeting $1_{n\times 1}^T\cdot x = 0$. As such, under the said assumptions, the only such vertex can be retrieved using linear programming.

math.OC

On a Geometric Interpretation Of the Subset Sum Problem

For $S \in \mathbb{N}^n$ and $T \in \mathbb{N}$, the Subset Sum Problem (SSP) $\exists^? x \in \{0,1\}^n $ such that $S^T\cdot x = T$ can be interpreted as the problem of deciding whether the intersection of the positive unit hypercube $Q_n = [0,1]^n$ with the hyperplane $S^T\cdot \left(x - \frac{S}{\|S\|^2 }\cdot T \right) = 0$ contains at least a vertex. In this paper, we give an algorithm of complexity $\mathcal{O}\left( \frac{1}ε\cdot n^b \right)$, for some absolute constant $b$, which either proves that there are no vertices in a slab of thickness $ε$ either finds a vertex in the slab of thickness $4\cdot ε$. It is shown that any vertex $P$ in a slab of thickness $ε$ meets $\left| \frac{S^T\cdot P}{T} - 1 \right| \leq ε$, therefore making the proposed algorithm a FPTAS for the SSP. The results are then applied to the study of the so called Simultaneous Subset-Sum Problem (SSSP).

cs.CG

A Deterministic Algorithm of Quasi-Polynomial Complexity for Clipped Cubes Volume Approximation

We give a deterministic method of quasi-polynomial complexity to approximate the volume of the intersection of the unit hypercube with two specific sets. The method can actually be applied (without losing the quasi-polynomial complexity) to compute the volume of the hypercube intersected with a fixed number of sets, described by equations of the form $\sum_{q=1}^n a_q(x_q) \leq b$, where $a_q : \mathbb{R} \to \mathbb{R}$ are polynomial functions and $b \in \mathbb{R}$. Note that the resulting sets are not necessarily convex. This type of equations describe, among others, half-spaces, balls and ellipsoids. We give detailed convergence and complexity analysis for the case in which the unit hypercube is clipped by balls of arbitrary radius but with centers whom distance to the unit hypercube is greater than $1$ (one).

math.OC

Fully Subexponential Time Approximation Scheme for Product Partition

In this paper we study the Product Partition Problem (PPP), i.e. we are given a set of $n$ natural numbers represented on $m$ bits each and we are asked if a subset exists such that the product of the numbers in the subset equals the product of the numbers not in the subset. Our approach is to obtain the integer factorization of each number. This is the subexponential step. We then form a matrix with the exponents of the primes and propose a novel procedure which modifies the given numbers in such a way that their integer factorization contains sufficient primes to facilitate the search for the solution to the partition problem, while maintaining a similar product. We show that the required time and memory to run the proposed algorithm is subexponential.

cs.DS

A Subexponential Reduction from Product Partition to Subset Sum

In this paper we study the Product Partition Problem (PPP), i.e. we are given a set of $n$ natural numbers represented on $m$ bits each and we are asked if a subset exists such that the product of the numbers in the subset equals the product of the numbers not in the subset. Our approach is to obtain the integer factorization of each number. This is the subexponential step. We then form a matrix with the exponents of the primes and show that the PPP has a solution iff some Subset Sum Problems have a common solution. Finally, using the fact that the exponents are not large we combine all the Subset Sum Problems in a single Subset Sum Problem (SSP) and show that its size is polynomial in $m,n$. We show that the PPP has a solution iff the final SSP has one.

math.CO

Tight Bounds for the Maximum Distance Over a Polytope to a Given Point

In this paper we study the problem of maximizing the distance to a given point $C_0$ over a polytope $\mathcal{P}$. Assuming that the polytope is circumscribed by a known ball we construct an intersection of balls which preserves the vertices of the polytope on the boundary of this ball, and show that the intersection of balls approximates the polytope arbitrarily well. Then, we use some known results regarding the maximization of distances to a given point over an intersection of balls to create a new polytope which preserves the maximizers to the original problem. Next, a new intersection of balls is obtained in a similar fashion, and as such, after a finite number of iterations, we conjecture, we end up with an intersection of balls over which we can maximize the distance to the given point. The obtained distance is shown to be a non trivial upper bound to the original distance. Tests are made with maximizing the distance to a random point over the unit hypercube up to dimension $n = 100$. Several detailed 2-d examples are also shown.

math.OC

On Efficient Approximation of the Maximum Distance to A Point Over an Intersection of Balls

In this paper we study the NP-Hard problem of maximizing the distance over an intersection of balls to a given point. We expand the results found in \cite{funcos1}, where the authors characterize the farthest in an intersection of balls $\mathcal{Q}$ to the given point $C_0$ by constructing some intersection of halfspaces. In this paper, by slightly modifying the technique found in literature, we characterize the farthest in an intersection of balls $\mathcal{Q}$ with another intersection of balls $\mathcal{Q}_1$. As such, going backwards, we are naturally able to find the given intersection of balls $\mathcal{Q}$ as the max indicator intersection of balls of another one $\mathcal{Q}_{-1}$. By repeating the process, we find a sequence of intersection of balls $(\mathcal{Q}_{i})_{i \in \mathbb{Z}}$, which has $\mathcal{Q}$ as an element, namely $\mathcal{Q}_{0}$ and show that $\mathcal{Q}_{-\infty} = \mathcal{B}(C_0,R_0)$ where $R_0$ is the maximum distance from $C_0$ to a point in $\mathcal{Q}$. As a final application of the proposed theory we give a polynomial algorithm for computing the maximum distance under an oracle which returns the volume of an intersection of balls, showing that the later is NP-Hard. Finally, we present a randomized method %of polynomial complexity which allows an approximation of the maximum distance.

cs.CG

A FPTAS for the Subset Sum Problem with Real Numbers

In this paper we study the subset sum problem with real numbers. Starting from the given problem, we formulate a quadratic maximization problem over a polytope which is eventually written as a distance maximization to a fixed point. For solving this, we provide a polynomial algorithm which maximizes the distance to a fixed point over a certain convex set. This convex set is obtained by intersecting the unit hypercube with two relevant half spaces. We show that in case the subset sum problem has a solution, our algorithm gives the correct maximum distance up to an arbitrary chosen precision. In such a case, we show that the obtained maximizer is a solution to the subset sum problem. Therefore, we compute the maximizer and upon analyzing it we can assert the feasibility of the subset sum problem.

math.OC

A Polynomial Algorithm for Some Relaxed Subset Sum Problems with Real Numbers

In this paper we study the subset sum problem with real numbers. Starting from the given problem, we formulate a quadratic maximization problem over a polytope, P, which is eventually written as a distance maximization to a fixed point over the polytope. Next, starting from the obtained polytope, we construct an intersection of balls which includes the polytope and show that in case the subset sum problem has a solution we can find it by maximizing the distance to the fixed point over the intersection of balls. That is, we show that the points which maximize the distance to the fixed point over the polytope are the same points which maximize the distance to the fixed point over the constructed intersection of balls. For the latter problem we give an original result which allows the characterization of the optimum points as follows: with the centers of the balls and the said fixed point we form a function whom sublevel sets are polytopes. As such we obtain a uni-parameter, family of polytopes. We show that by increasing this parameter from 0 to a finite maximum value (which is computed through a convex optimization problem), the polytopes in the family evolve from initially containing the intersection of balls towards three possible outcomes: a) included in the interior of the intersection of balls b) included in the interior of the complementary of the intersection of balls c) the border of the intersection of balls and the polytope of maximum parameter share at least a point. Then we show that the maximum distance to the fixed point over the intersection of balls is given by a) the smallest parameter for which the polytopes enter the intersection of balls, b) the largest parameter for which the polytopes still share points with the intersection of balls c) the maximum value of the parameter. ...

math.OC

A Quasi-Polynomial Algorithm for Subset-Sum Problems with At Most One Solution

In this paper we study the problem of maximizing the distance to a given point over an intersection of balls. It was already known that this problem can be solved in polynomial time and space if the given point is not in the convex hull of the balls centers. The cases where the given point is in the convex hull of the balls centers include all NP-complete problems as we show. Some novel results are given in this area. A novel projection algorithm is developed then applied in the context of the Subset Sum Problem (SSP). Under the assumption that the SSP has at most one solution, we provide a quasi-polynomial algorithm, which decreases the radius of an initial ball containing the solution to the SSP. We perform some numerical tests which show the effectiveness of the proposed algorithm.

math.OC

On Maximizing the Distance to a Given Point over an Intersection of Balls II

In this paper the problem of maximizing the distance to a given fixed point over an intersection of balls is considered. It is known that this problem is NP complete in the general case, since any subset sum problem can be solved upon solving a maximization of the distance over an intersection of balls to a point inside the convex hull. The general context is: in [1] it is shown that exists a polynomial algorithm which always solves the maximization problem if the given point is outside the convex hull of the centers of the balls. Naturally one asks if there is a polynomial algorithm which solves the problem for a point inside the convex hull. A conjecture stated in a previous paper, [1] is proved, under slightly stronger conditions. The proven conjecture allows a polynomial algorithm for points on the facets of the convex hull and shows that such points share the maximizer with all the points in a small enough ball centered at it, thus including points in the interior of the convex hull of the ball centers.

math.OC

On Global Maximization of Bounded Hessian Functions over Strongly Convex Domains

In this paper we present two frameworks in which global maximization of a bounded hessian function over a strongly convex set can be reduced to convex optimization. The first presented framework is a continuation of one of our previous papers [11]. We improve the results and give an explicit algorithm for the computation in polynomial time of the farthest point in a finite intersection of n-disks to $C \in \mathbb{R}^{n \times 1}$ under the requirement that $C$ does not belong to the convex hull of the centers of the n-disks. Finally, in order to overcome this limitation we present a second framework which characterizes the furthest in the finite intersection of n-disks with $C$ in the convex hull. Unfortunately this second framework requires the ability to decide if a polytope that we define is included in the intersection, which is hard in general. However, as a particular application of our second framework we are able solve in P time some instances of the subset sum problem with real entries: given a set of real numbers decide if there is a subset which adds up to zero.

math.OC

Unconstraint minimization of continuous convex functions. Application to LP

Our contribution in this paper is two folded. We consider first the case of linear programming with real coefficients and give a method which allows the computation of a new upper bound on the distance from the origin to a feasible point. Next we present an application of the ellipsoid method to form a novel algorithm which allows one to search for the continuous convex functions minimum without the prior knowledge on the search radius. If stopped early, the proposed algorithm can give proofs that the optimal value has not been reached yet, hence the user can opt for more iterations. However, if prior guarantees exist on the existence of an optimum point in a given ball, the algorithm is guaranteed to find it. For such a case we prove a polynomial upper bound on the number of flops required to obtain the solution. The presented algorithm is then applied to linear programming. We further develop our algorithm and provide a method to answer the feasibility question of linear programs with real coefficients in a number of flops bounded above by a polynomial in the number of variables and the number of constraints. However, in case of feasibility, our method does not generate an actual feasible point. For obtaining such a point, we have to make some assumptions on the subgradients of a certain function.

math.OC

A new proof for the exact values of $ζ(2k)$ for $k \in \mathbb{N}$

We establish a connection between a function and a series representation using a similar technique with that that Euler used to solve the Basel problem. Our result concerns a more general series from which one can obtain $ζ(2k)$ as a limit case. We also are able to prove the well known result expressing $ζ(2k)$ with Bernoulli numbers as an application.

math.NT