An analytic center quadratic cut method for the convex quadratic feasibility problem

 We consider a quadratic cut method based on analytic centers for two cases of convex quadratic feasibility problems. In the first case, the convex set is defined by a finite yet large number, N, of convex quadratic inequalities. We extend quadratic cut algorithm of Luo and Sun [3] for solving such problems by placing or translating the quadratic cuts directly through the current approximate center. We show that, in terms of total number of addition and translation of cuts, our algorithm has the same polynomial worst case complexity as theirs [3]. However, the total number of steps, where steps consist of (damped) Newton steps, function evaluations and arithmetic operations, required to update from one approximate center to another is , where ε is the radius of the largest ball contained in the feasible set. In the second case, the convex set is defined by an infinite number of certain strongly convex quadratic inequalities. We adapt the same quadratic cut method for the first case to the second one. We show that in this case the quadratic cut algorithm is a fully polynomial approximation scheme. Furthermore, we show that, at each iteration, k, the total number steps (as described above) required to update from one approximate center to another is at most , with ε as defined above. Received: April 2000 / Accepted: June 2002 Published online: September 5, 2002 Key words. convex quadratic feasibility problem – interior-point methods – analytic center – quadratic cuts – potential function     

Polynomial Hierarchy, Betti Numbers, and a Real Analogue of Toda’s Theorem

Toda (in SIAM J. Comput. 20(5):865–877, 1991) proved in 1989 that the (discrete) polynomial time hierarchy, PH, is contained in the class P ^#P , namely the class of languages that can be decided by a Turing machine in polynomial time given access to an oracle with the power to compute a function in the counting complexity class #P. This result, which illustrates the power of counting, is considered to be a seminal result in computational complexity theory. An analogous result in the complexity theory over the reals (in the sense of Blum–Shub–Smale real machines in Bull. Am. Math. Soc. (NS) 21(1): 1–46, 1989) has been missing so far. In this paper we formulate and prove a real analogue of Toda’s theorem. Unlike Toda’s proof in the discrete case, which relied on sophisticated combinatorial arguments, our proof is topological in nature. As a consequence of our techniques, we are also able to relate the computational hardness of two extremely well-studied problems in algorithmic semi-algebraic geometry: the problem of deciding sentences in the first-order theory of the reals with a constant number of quantifier alternations, and that of computing Betti numbers of semi-algebraic sets. We obtain a polynomial time reduction of the compact version of the first problem to the second. This latter result may be of independent interest to researchers in algorithmic semi-algebraic geometry.     

Lower bounds on the worst-case complexity of some oracle algorithms

To give a proper definition of the complexity of very general computational problems such as optimization problems over arbitrary independence systems or fixed-point problems for continuous functions, it is useful to consider the input for these problems as “oracles” R which can be called by the algorithms for some values x ∈ X and which then give back some information R(x) about x, e.g. whether x belongs to the independence system or the point into which x is mapped by the continuous function. A lower bound on the complexity of an algorithm using an oracle R is the number of calls on R in the worst case. Using this technique it is shown that there is no polynomial approximative algorithm for the maximization problem over a general independence system which has a better worst-case behaviour than the greedy algorithm. Moreover several formalizations of the problem of approximating a fixed point of a continuous function are considered, and it is shown that none of these problems can be solved by a bounded algorithm.     

Palindromic quadratization and structure-preserving algorithm for palindromic matrix polynomials of even degree

In this paper, we propose a palindromic quadratization approach, transforming a palindromic matrix polynomial of even degree to a palindromic quadratic pencil. Based on the (S+ S^-1){(\mathcal{S}+ \mathcal{S}^{-1})} -transform and Patel’s algorithm, the structure-preserving algorithm can then be applied to solve the corresponding palindromic quadratic eigenvalue problem. Numerical experiments show that the relative residuals for eigenpairs of palindromic polynomial eigenvalue problems computed by palindromic quadratized eigenvalue problems are better than those via palindromic linearized eigenvalue problems or polyeig{{\texttt {polyeig}}} in MATLAB.     

On scheduling with the non-idling constraint

In this paper, we give an overview of the main results obtained on the complexity of scheduling under the non-idling constraint, i.e, when the jobs assigned to each machine must be processed with no intermediate delay. That constraint is met in practice when the cost of intermediate idle time is too high due to the idle time itself and/or the machine restarting. The non idling constraint is a strong constraint that often needs a new solving approach and most results about classical scheduling problems do not easily extend to the non-idling variant of the problem. In this survey, we mainly consider the non-idling variants of the basic scheduling problems. So, we first present basic properties, complexity results and some algorithms concerning the one-machine non-idling scheduling problem. Then we consider the $m$ -machine non idling scheduling problem. We show that a few basic problems may be solved by rather easy extensions of the algorithm solving their classical counterpart. However, the complexity status of the non idling version of quite easy polynomial basic problems remains an open question. We finally consider a more constrained version of non-idling, called the “homogeneously non idling” constraint, where for any subset of machines, the union of their busy intervals must make an interval and we present the structural property that leads to a polynomial algorithm for unit time jobs and a weak precedence. We conclude by giving some research directions that seem quite interesting to study both for theoretical and practical issues.     

Time complexity of single machine scheduling with stochastic precedence constraints

This paper deals with single machine scheduling problems with stochastic precedence relations (so calledGERT networks). Until now most investigations on such problems, dealt with algorithms running in polynomial time. On the other hand, for scheduling problems with deterministic precedence relations exist a lot of results about time complexity. Therefore, the object of this paper is to consider time complexity of scheduling problems with stochastic precedence constraints and to describe the boundary between theNP-hard problems and those which can be solved in polynomial time.     

Inverse median location problems with variable coordinates

Given n points in \mathbbR^d{\mathbb{R}^d} with nonnegative weights, the inverse 1-median problem with variable coordinates consists in changing the coordinates of the given points at minimum cost such that a prespecified point in \mathbbR^d{\mathbb{R}^d} becomes the 1-median. The cost is proportional to the increase or decrease of the corresponding point coordinate. If the distances between points are measured by the rectilinear norm, the inverse 1-median problem is NP{\mathcal{NP}}-hard, but it can be solved in pseudo-polynomial time. Moreover, a fully polynomial time approximation scheme exists in this case. If the point weights are assumed to be equal, the corresponding inverse problem can be reduced to d continuous knapsack problems and is therefore solvable in O(nd) time. In case that the squared Euclidean norm is used, we derive another efficient combinatorial algorithm which solves the problem in O(nd) time. It is also shown that the inverse 1-median problem endowed with the Chebyshev norm in the plane is NP{\mathcal{NP}}-hard. Another pseudo-polynomial algorithm is developed for this case, but it is shown that no fully polynomial time approximation scheme does exist.     

A capacity-rounding algorithm for the minimum-cost circulation problem: A dual framework of the Tardos algorithm

Recently, É. Tardos gave a strongly polynomial algorithm for the minimum-cost circulation problem and solved the open problem posed in 1972 by J. Edmonds and R.M. Karp. Her algorithm runs in O(m ² T(m, n) logm) time, wherem is the number of arcs,n is the number of vertices, andT(m, n) is the time required for solving a maximum flow problem in a network withm arcs andn vertices. In the present paper, taking an approach that is a dual of Tardos's, we also give a strongly polynomial algorithm for the minimum-cost circulation problem. Our algorithm runs in O(m ² S(m, n) logm) time and reduces the computational complexity, whereS(m, n) is the time required for solving a shortest path problem with a fixed origin in a network withm arcs,n vertices, and a nonnegative arc length function. The complexity is the same as that of Orlin's algorithm, recently developed by efficiently implementing the Edmonds-Karp scaling algorithm.     

An active index algorithm for the nearest point problem in a polyhedral cone

We consider the problem of finding the nearest point in a polyhedral cone C={x∈R ⁿ :D x≤0} to a given point b∈R ⁿ , where D∈R ^m×n . This problem can be formulated as a convex quadratic programming problem with special structure. We study the structure of this problem and its relationship with the nearest point problem in a pos cone through the concept of polar cones. We then use this relationship to design an efficient algorithm for solving the problem, and carry out computational experiments to evaluate its effectiveness. Our computational results show that our proposed algorithm is more efficient than other existing algorithms for solving this problem.     

An Infeasible Mizuno–Todd–Ye Type Algorithm for Convex Quadratic Programming with Polynomial Complexity

Infeasible interior point methods have been very popular and effective. In this paper, we propose a predictor–corrector infeasible interior point algorithm for convex quadratic programming, and we prove its convergence and analyze its complexity. The algorithm has the polynomial numerical complexity with O(nL)-iteration.     

Approximation algorithms for scheduling unrelated parallel machines

We consider the following scheduling problem. There arem parallel machines andn independent jobs. Each job is to be assigned to one of the machines. The processing of jobj on machinei requires timep _ij . The objective is to find a schedule that minimizes the makespan.Our main result is a polynomial algorithm which constructs a schedule that is guaranteed to be no longer than twice the optimum. We also present a polynomial approximation scheme for the case that the number of machines is fixed. Both approximation results are corollaries of a theorem about the relationship of a class of integer programming problems and their linear programming relaxations. In particular, we give a polynomial method to round the fractional extreme points of the linear program to integral points that nearly satisfy the constraints.In contrast to our main result, we prove that no polynomial algorithm can achieve a worst-case ratio less than 3/2 unlessP = NP. We finally obtain a complexity classification for all special cases with a fixed number of processing times.A preliminary version of this paper appeared in theProceedings of the 28th Annual IEEE Symposium on the Foundations of Computer Science (Computer Society Press of the IEEE, Washington, D.C., 1987) pp. 217–224.     

The connectedness of the real locus of the Hilbert scheme ofP r

Summary Let χ be a numerical polynomial. Here we prove the connectedness of the real locus Hilb χ(P ^r )(R) of the Hilbert scheme parametrizing all the subschemes ofP ^r with χ as Hilbert polynomial.

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Sunto Sia χ un polinomio numerico. In questa nota si dimostra la connessione della parte reale Hilb χ(P ^r )(R) dello schema di Hilbert che parametrizza tutti i sottoschemi diP ^r che hanno χ come polinomio di Hilbert.

     

A branch-and-reduce approach to global optimization

This paper presents valid inequalities and range contraction techniques that can be used to reduce the size of the search space of global optimization problems. To demonstrate the algorithmic usefulness of these techniques, we incorporate them within the branch-and-bound framework. This results in a branch-and-reduce global optimization algorithm. A detailed discussion of the algorithm components and theoretical properties are provided. Specialized algorithms for polynomial and multiplicative programs are developed. Extensive computational results are presented for engineering design problems, standard global optimization test problems, univariate polynomial programs, linear multiplicative programs, mixed-integer nonlinear programs and concave quadratic programs. For the problems solved, the computer implementation of the proposed algorithm provides very accurate solutions in modest computational time.     

Witt equivalence of local and global fields of characteristic 2

ABSTRACT

In this note it is proved that certain level sets of some real proper polynomial maps are nothing but spheres. As an application of this, we provide new proofs of Theorems 1.1, 1.2 and of the fundamental theorem of algebra. In addition, we show that every strictly convex (concave) polynomial map is proper. The latter implies that every real polynomial map g(x): R ⁿ  → R ⁿ , whose Jacobian matrix is symmetric and has nonzero eigenvalues of the same sign, is a homeomorphism of R ⁿ onto R ⁿ .     

Pipes, Cigars, and Kreplach: the Union of Minkowski Sums in Three Dimensions

Let Ω be a set of pairwise-disjoint polyhedral obstacles in R ³ with a total of n vertices, and let B be a ball in R ³. We show that the combinatorial complexity of the free configuration space F of B amid Ω:, i.e., (the closure of) the set of all placements of B at which B does not intersect any obstacle, is O(n ^2+ε ), for any ε >0; the constant of proportionality depends on ε. This upper bound almost matches the known quadratic lower bound on the maximum possible complexity of F . The special case in which Ω is a set of lines is studied separately. We also present a few extensions of this result, including a randomized algorithm for computing the boundary of F whose expected running time is O(n ^2+ε ). Received July 6, 1999, and in revised form April 25, 2000. Online publication August 18, 2000.     

An optimal multivariate spline method of recovery of twice differentiable functions

A continuous quadratic polynomial spline of several variables is constructed. It solves the optimal recovery problem studied by V.F. Babenko, S.V. Borodachov, and D.S. Skorokhodov for the class of functions defined on a convex polytope in R ^d , whose second derivatives in any direction are uniformly bounded, and for a periodic analogue of this class. The information consists of the values and gradients of the function at some finite set of nodes in R ^d .     

Computing the Top Betti Numbers of Semialgebraic Sets Defined by Quadratic Inequalities in Polynomial Time

For any ℓ>0, we present an algorithm which takes as input a semi-algebraic set, S, defined by P ₁≤0,…,P _s ≤0, where each P _i ∈R[X ₁,…,X _k ] has degree≤2, and computes the top ℓ Betti numbers of S, b _k−1(S),…,b _k−ℓ (S), in polynomial time. The complexity of the algorithm, stated more precisely, is . For fixed ℓ, the complexity of the algorithm can be expressed as , which is polynomial in the input parameters s and k. To our knowledge this is the first polynomial time algorithm for computing nontrivial topological invariants of semialgebraic sets in R ^k defined by polynomial inequalities, where the number of inequalities is not fixed and the polynomials are allowed to have degree greater than one. For fixed s, we obtain, by letting ℓ=k, an algorithm for computing all the Betti numbers of S whose complexity is . An erratum to this article can be found at     

Conjugacy Classes and Invariant Subrings of R-Automorphisms of R[x]

We consider the group G of R-automorphisms of the polynomial ring R[x] in the case where the ring R has nonzero nilpotent elements. Little is known about G in this case, and because of the importance of G in understanding questions involving the polynomial ring R[x], we initiate here several lines of investigation. We do this by examining in detail examples involving the ring of integers modulo n. If R is a local ring with maximal ideal m such that R/m = ?₂ and m ² = (0), we describe more explicitly the structure of G and determine all rings of invariants of R[x] with respect to subgroups of G.     

Minimizing the total completion time in a unit-time open shop with release times

We consider the problem of minimizing the total completion time in a unit-time open shop with release times where the number of machines is constant. Brucker and Krämer (1994) proved that this problem is solvable in polynomial time. However, the time complexity of the algorithm presented there is a polynom of a very high degree and, thus, the algorithm is not practicable even for a small number of machines. We give an O(n²) algorithm for the considered problem which is based on dynamic programming. The result is applied to solve a previously open problem with a special resource constraint raised by De Werra et al. (1991).