Polynomial-time interior-point algorithm based on a local self-concordant finite barrier function

The choice of self-concordant functions is the key to efficient algorithms for linear and quadratic convex optimizations, which provide a method with polynomial-time iterations to solve linear and quadratic convex optimization problems. The parameters of a self-concordant barrier function can be used to compute the complexity bound of the proposed algorithm. In this paper, it is proved that the finite barrier function is a local self-concordant barrier function. By deriving the local values of parameters of this barrier function, the desired complexity bound of an interior-point algorithm based on this local self-concordant function for linear optimization problem is obtained. The bound matches the best known bound for small-update methods.

Polynomial-time algorithm for the legal firing sequences problem of a type of synchronous composition Petri nets

As far as we know, the testing problem of legal firing sequence is NP-complete for gener-al Petri net, the related results of this problem on the polynomial-time solvability are limited only to some special net classes, such as persistent Petri nets, conflict-free Petri nets and state machine Petri nets. In this paper, the language properties of synchronous composition net are discussed. Based on these results, the testing algorithm polynomial-time complexity for legal firing sequence is proposed. Therefore, net classification of polynomial-time solvability for testing legal firing sequence is extended.

Polynomial-time Hierarchies on Some Classes of Functions (Ⅱ)

This paper continues to study these hierarchies, the probably impossible relationships within and between them, and gives some complete functions for the classes.

Polynomial-Time Hierarchies on Some Classes of Functions (Ⅰ)

Four polynomial-time hierarchies on functions are introduced, which are considered to be generalizations of Valiant’s counting function class #P, class Span-P introduced by Kobler et al., Krentel’s optimization function class Opt-P, and F2p. It is shown that our polynomial hierarchies of optimization functions are the same as that defined by Krentel. The relationships within every hierarchy and between them are studied.

THE POLYNOMIAL-TIME HIERARCHY AND ORACLE SET A∈PH/poly

Ⅰ. INTRODUCTIONA central problem in computational complexity is whether or not the polynomial-time hierarchy is proper. Balcázar, Book and Schning have studied this problem by considering relativization with respect to sparse sets and proved the following results:

ON THE OPTIMAL MULTI-RATE THROUGHPUT FOR MULTICAST WITH NETWORK CODING

This paper investigates the maximal achievable multi-rate throughput problem of a multicast ses-sion at the presence of network coding. Deviating from previous works which focus on single-rate network coding, our work takes the heterogeneity of sinks into account and provides multiple data layers to address the problem. Firstly formulated is the maximal achievable throughput problem with the assumption that the data layers are independent and layer rates are static. It is proved that the problem in this case is, unfortunately, Non-deterministic Polynomial-time (NP)-hard. In addition, our formulation is extended to the problems with dependent layers and dynamic layers. Furthermore, the approximation algorithm which satisfies certain fair-ness is proposed.

DISCUSSION ON KARMARKAR'S METHOD FOR SOLVING UNSTANDARD MODEL.

In this paper,a discussion on the new polynomial-time algorithm for linearprogramming as proposed by Karmarkar.N.is presented.The problem is solved when aninitial feasible solution is unknown.For the case where the optimum value of the objectivefunction is unknown,the reasonableness and feasibility of the sliding objective functionmethod are proved.And a method of modifying the parameters is put forward.

AN EFFICIENT BIT COMMITMENT SCHEME BASED ON FACTORING ASSUMPTION

Recently, many bit commitment schemes have been presented. This paper presents a new practical bit commitment scheme based on Schnorr's one-time knowledge proof scheme,where the use of cut-and-choose method and many random exam candidates in the protocols are replaced by a single challenge number. Therefore the proposed bit commitment scheme is more efficient and practical than the previous schemes In addition, the security of the proposed scheme under factoring assumption is proved, thus the cryptographic basis of the proposed scheme is clarified.

On Fixed-Parameter Solvability of the Minimax Path Location Problem

The minimax path location problem is to find a path P in a graph G such that the maximum distance d_(G)(v,P)from every vertex v∈V(G)to the path P is minimized.It is a well-known NP-hard problem in network optimization.This paper studies the fixed-parameter solvability,that is,for a given graph G and an integer k,to decide whether there exists a path P in G such that max v∈V(G)d_(G)(v,P)≤k.If the answer is affirmative,then graph G is called k-path-eccentric.We show that this decision problem is NP-complete even for k=1.On the other hand,we characterize the family of 1-path-eccentric graphs,including the traceable,interval,split,permutation graphs and others.Furthermore,some polynomially solvable special graphs are discussed.

Solution to the Balanced Academic Curriculum Problem Using Tabu Search

The Balanced Academic Curriculum Problem （BACP） is a constraint satisfaction problem classified as （Non-deterministic Polynomial-time Hard） NP-Hard. This problem consists in the allocation of courses in the periods that are part of a curriculum such that the prerequisites are satisfied and the load of courses is balanced for the students. This paper presents the solution for a modified BACP where the academic loads and number of curses may be the same or different for each one of the periods and allows having some courses in a specific period. This problem is modeled as an integer programming problem and is proposed the use of Tabu search with short-term memory for its solution because it is not possible to find solutions for all the instances of this modified problem with an exact method.

SAT in P Does Not Imply Chaos in the Security System

There are a large number of papers that claim that there are problems that once solved lead to an efficient solution of a wide range of problems, classified as NP. In this paper we will not only question the existence of this class of NP-co problems, but we will also explain their limitations in engineering and give a polynomial-time solution to SAT, one of these emblematic problems. The resolution will be so trivial that it will even be possible to practice it on paper.

Increasing the Maximum Capacity Path in a Network and Its Application for Improving the Connection Between Two Routers

Abstract:This paper addresses the problem of improving the optimal value of the Maximum Capacity Path(MCP)through expansion in a flexible network,and minimizing the involved costs.The only condition applied to the cost functions is to be non-decreasing monotone.This is a non-restrictive condition,reflecting the reality in practice,and is considered for the first time in the literature.Moreover,the total cost of expansion is a combination of max-type cost(e.g.,for supervision)and sum-type cost(e.g.for building infrastructures,price of materials,price of labor,etc.).For this purpose,two types of strategies are combined:(l)increasing the capacity of the existing arcs,and(l)adding potential new arcs.Two different problems are introduced and solved.Both the problems have immediate applications in Internet routing infrastructure.The first one is to extend the network,so that the capacity of an McP in the modified network becomes equal to a prescribed value,therefore the cost of modifications is minimized.A strongly polynomial-time algorithm is deduced to solve this problem.The second problem is a network expansion under a budget constraint,so that the capacity of an McP is maximized.A weakly polynomial-time algorithm is presented to deal with it.In the special case when all the costs are linear,a Meggido's parametric search technique is used to develop an algorithm for solving the problem in strongly polynomial time.This new approach has a time complexity of O(n^(4)),which is better than the time complexity of O(n4 log(n)of the previously known method from literature.

The Minimum Centroid Branch Spanning Tree Problem

For a spanning tree T of graph G,the centroid of T is a vertex v for which the largest component of T-v has as few vertices as possible.The number of vertices of this component is called the centroid branch weight of T.The minimum centroid branch spanning tree problem is to find a spanning tree T of G such that the centroid branch weight is minimized.In application to design of communication networks,the loads of all branches leading from the switch center should be as balanced as possible.In this paper,we prove that the problem is strongly NP-hard even for bipartite graphs.Moreover,the problem is shown to be polynomially solvable for split graphs,and exact formulae for special graph familis,say Kn_(1),n_(2),...,n_(k)and P_(m)×P_(n),are presented.

Primal-dual Interior-point Algorithms for Second-order Cone Optimization Based on a New Parametric Kernel Function

A class of polynomial primal-dual interior-point algorithms for second-order cone optimization based on a new parametric kernel function, with parameters p and q, is presented. Its growth term is between linear and quadratic. Some new tools for the analysis of the algorithms are proposed. The complexity bounds of O（√Nlog N log N/ε） for large-update methods and O（√Nlog N/ε） for smallupdate methods match the best known complexity bounds obtained for these methods. Numerical tests demonstrate the behavior of the algorithms for different results of the parameters p and q.

Comparison of Semantics of Disjunctive Logic Programs Based on Model-Equivalent Reduction

In this paper, it is shown that stable model semantics, perfect model semantics, and partial stable model semantics of disjunctive logic programs have the same expressive power with respect to the polynomial-time model-equivalent reduction. That is, taking perfect model semantics and stable model semantic as an example, any logic program P can be transformed in polynomial time to another logic program P＇ such that perfect models （resp. stable models） of P i-i correspond to stable models （resp. perfect models） of P＇, and the correspondence can be computed also in polynomial time. However, the minimal model semantics has weaker expressiveness than other mentioned semantics, otherwise, the polynomial hierarchy would collapse to NP.

Infeasible-interior-point algorithm for a class of nonmonotone complementarity problems and its computational complexity

This paper presents an infeasible-interior-point algorithm for aclass of nonmonotone complementarity problems, and analyses its convergence and computational complexity. The results indicate that the proposed algorithm is a polynomial-time one.

Linear Arboricity of Outer-1-Planar Graphs

A graph is outer-1-planar if it can be drawn in the plane so that all vertices are on the outer face and each edge is crossed at most once.Zhang et al.(Edge covering pseudo-outerplanar graphs with forests,Discrete Math 312:2788-2799,2012;MR2945171)proved that the linear arboricity of every outer-1-planar graph with maximum degree△is exactly[△/2] provided that△=3or△≥5 and claimed that there are outer-1-planar graphs with maximum degree △=4 and linear arboricity[[(O+1)/2]=3.It is shown in this paper that the linear arboricity of every outer-1-planar graph with maximum degree 4 is exactly 2 provided that it admits an outer-1-planar drawing with crossing distance at least 1 and crossing width at least 2,and moreover,none of the above constraints on the crossing distance and Crossing width can be removed..Besides,a polynomial-time algorithm for constructing a path-2-coloring(i.e.,an edge 2-coloring such that each color class induces a linear forest,a disjoint union of paths)of such an outer-1-planar drawing is given.

Risk Models for the Prize Collecting Steiner Tree Problems with Interval Data

Given a connected graph G=（V,E）with a nonnegative cost on each edge in E,a nonnegative prize at each vertex in V,and a target set V′V,the Prize Collecting Steiner Tree（PCST）problem is to find a tree T in G interconnecting all vertices of V′such that the total cost on edges in T minus the total prize at vertices in T is minimized.The PCST problem appears frequently in practice of operations research.While the problem is NP-hard in general,it is polynomial-time solvable when graphs G are restricted to series-parallel graphs.In this paper,we study the PCST problem with interval costs and prizes,where edge e could be included in T by paying cost xe∈[c e,c＋e]while taking risk（c＋e xe）/（c＋e c e）of malfunction at e,and vertex v could be asked for giving a prize yv∈[p v,p＋v]for its inclusion in T while taking risk（yv p v）/（p＋v p v）of refusal by v.We establish two risk models for the PCST problem with interval data.Under given budget upper bound on constructing tree T,one model aims at minimizing the maximum risk over edges and vertices in T and the other aims at minimizing the sum of risks over edges and vertices in T.We propose strongly polynomial-time algorithms solving these problems on series-parallel graphs to optimality.Our study shows that the risk models proposed have advantages over the existing robust optimization model,which often yields NP-hard problems even if the original optimization problems are polynomial-time solvable.

Nonuniform Lowness and Strong Nonuniform Lowness

The concepts of the nonuniform and strong nonuniform lownesss are in-troduced. Those notions provide a uniform framework to study connectionsbetween the polynomiaLtime hierarchy and sparse sets.

Approximation Algorithms for Vertex Happiness

We investigate the maximum happy vertices(MHV)problem and its complement,the minimum unhappy vertices(MUHV)problem.In order to design better approximation algorithms,we introduce the supermodular and submodular multi-labeling(SUP-ML and SUB-ML)problems and show that MHV and MUHV are special cases of SUP-ML and SUB-ML,respectively,by rewriting the objective functions as set functions.The convex relaxation on the I ovasz extension,originally presented for the submodular multi-partitioning problem,can be extended for the SUB-ML problem,thereby proving that SUB-ML(SUP-ML,respectively)can be approximated within a factorof2-2/k(2/k,respectively),where k is the number of labels.These general results imply that MHV and MUHV can also be approximated within factors of 2/k and 2-2/k,respectively,using the same approximation algorithms.For the MUHV problem,we also show that it is approximation-equivalent to the hypergraph multiway cut problem;thus,MUHV is Unique Games-hard to achieve a(2-2/k-e)-approximation,for anyε>0.For the MHV problem,the 2/k-approximation improves the previous best approximation ratio max{1/k,1/(△+1/g(△)},where△is the maximum vertex degree of the input graph and g(△)=(√△+√△+1)2△>4△2.We also show that an existing LP relaxation for MHV is the same as the concave relaxation on the Lovasz extension for SUP-ML;we then prove an upper bound of 2/k on the integrality gap of this LP relaxation,which suggests that the 2/k-approximation is the best possible based on this LP relaxation.Lastly,we prove that it is Unique Games-hard to approximate the MHV problem within a factor of S2(log2 k/k).