The graphical relaxation: A new framework for the symmetric traveling salesman polytope

A present trend in the study of theSymmetric Traveling Salesman Polytope (STSP(n)) is to use, as a relaxation of the polytope, thegraphical relaxation (GTSP(n)) rather than the traditionalmonotone relaxation which seems to have attained its limits. In this paper, we show the very close relationship between STSP(n) and GTSP(n). In particular, we prove that every non-trivial facet of STSP(n) is the intersection ofn + 1 facets of GTSP(n),n of which are defined by the degree inequalities. This fact permits us to define a standard form for the facet-defining inequalities for STSP(n), that we calltight triangular, and to devise a proof technique that can be used to show that many known facet-defining inequalities for GTSP(n) define also facets of STSP(n). In addition, we give conditions that permit to obtain facet-defining inequalities by composition of facet-defining inequalities for STSP(n) and general lifting theorems to derive facet-defining inequalities for STSP(n +k) from inequalities defining facets of STSP(n).Partially financed by P.R.C. Mathématique et Informatique.     

A class of Hamiltonian and edge symmetric Cayley graphs on symmetric groups

Abstract. Let Sn be the symmetric group     

Recognition of some symmetric groups by the set of the order of their elements

For a finite group G, let π_e(G) be the set of order of elements in G and denote S _n the symmetric group on n letters. We will show that if π_e(G ) = π_e(H), where H is S _p or S _p+1 and p is a prime with 50 < p < 100, then G ≅ H. This revised version was published online in August 2006 with corrections to the Cover Date.     

Facet identification for the symmetric traveling salesman polytope

Several procedures for the identification of facet inducing inequalities for the symmetric traveling salesman polytope are given. An identification procedure accepts as input the support graph of a point which does not belong to the polytope, and returns as output some of the facet inducing inequalities violated by the point. A procedure which always accomplishes this task is calledexact, otherwise it is calledheuristic. We give exact procedures for the subtour elimination and the 2-matching constraints, based on the Gomory—Hu and Padberg—Rao algorithms respectively. Efficient reduction procedures for the input graph are proposed which accelerate these two algorithms substantially. Exact and heuristic shrinking conditions for the input graph are also given that yield efficient procedures for the identification of simple and general comb inequalities and of some elementary clique tree inequalities. These procedures constitute the core of a polytopal cutting plane algorithm that we have devised and programmed to solve a substantial number of large-scale problem instances with sizes up to 2392 nodes to optimality.Partial financial support by NSF grant DMS8508955 and ONR grant R&T4116663.Work done while visiting New York University. Partial financial support by a New York University Research Challenge Fund grant and ONR grant R&T4116663.     

A black-box group algorithm for recognizing finite symmetric and alternating groups, I

We present a Las Vegas algorithm which, for a given black-box group known to be isomorphic to a symmetric or alternating group, produces an explicit isomorphism with the standard permutation representation of the group. This algorithm has applications in computations with matrix groups and permutation groups.

In this paper, we handle the case when the degree of the standard permutation representation is part of the input. In a sequel, we shall treat the case when the value of is not known in advance.

As an important ingredient in the theoretical basis for the algorithm, we prove the following result about the orders of elements of : the conditional probability that a random element is an -cycle, given that , is at least .

     

A multicriteria approach for optimizing bus schedules and school starting times

In many rural counties pupils on their way to school are a large, if not the largest group of customers for public mass transit. Hence an effective optimization of public mass transit in these regions must include the traffic caused by pupils. Besides a change in the schedules of the buses and the starting times of the trips, the school starting time may become an integral part of the planning process. We discuss the legal framework for this optimization problem in German states and counties and present a multi-objective mixed-integer linear programming formulation for the simultaneous specification of school and trip starting times. For its solution, we develop a two-stage decomposition heuristic and apply it to practical data sets from three different rural German counties.     

Improved Large-Step Markov Chain Variants for the Symmetric TSP

The large-step Markov chain (LSMC) approach is the most effective known heuristic for large symmetric TSP instances; cf. recent results of [Martin, Otto and Felten, 1991] and [Johnson, 1990]. In this paper, we examine relationships among (i) the underlying local optimization engine within the LSMC approach, (ii) the kick move perturbation that is applied between successive local search descents, and (iii) the resulting LSMC solution quality. We find that the traditional double-bridge kick move is not necessarily optimum: stronger local optimization engines (e.g., Lin-Kernighan) are best matched with stronger kick moves. We also propose use of an adaptive temperature schedule to allow escape from deep basins of attraction; the resulting hierarchical LSMC variant outperforms traditional LSMC implementations that use uniformly zero temperatures. Finally, a population-based LSMC variant is studied, wherein multiple solution paths can interact to achieve improved solution quality.     

A lower bound on the vertices of Specht modules for symmetric groups

In this paper we study the vertices of indecomposable Specht modules for symmetric groups. For any given indecomposable non-projective Specht module, the main theorem of the article describes a p-subgroup contained in its vertex. The theorem generalizes and improves an earlier result due to Wildon in [13].     

Analysis of Random Restart and Iterated Improvement for Global Optimization with Application to the Traveling Salesman Problem

The optimization method employing iterated improvement with random restart (I2R2) is studied. Associated with each instance of an I2R2 search is a fundamental polynomial, in which the coefficient p_k is the probability of starting a search k improvement steps from a local minimum. The positive root of f can be used to calculate the convergence and speedup properties of that instance.Since the coefficients of f are naturally related to the search, it is possible to estimate them online if an a priori estimate of the size of the goal basin is available, for example by analysis or prior experience. In this case, the runtime statistical estimate of converges many times faster than the estimates of the coefficients themselves.The foregoing is illustrated with an application to the traveling salesman problem (TSP) using the k-change as the improvement discipline. Among other things, it is shown that a k-change improvement can be affected by k 2-changes, that =1 for convex city sets, and that good estimates of can be made from a reduced TSP related to the given one.This research was partially supported by the National Sciences and Engineering Research Council of Canada (NSERC) in the form of a discovery grant. The authors thank the referees for helpful suggestions and timeliness.     

A criterion for the logarithmic differential operators to be generated by vector fields

We study divisors in a complex manifold in view of the property that the algebra of logarithmic differential operators along the divisor is generated by logarithmic vector fields. We give

• a sufficient criterion for the property,
• a simple proof of F.J. Calderón-Moreno's theorem that free divisors have the property,
• a proof that divisors in dimension with only isolated quasi-homogeneous singularities have the property,
• an example of a nonfree divisor with nonisolated singularity having the property,
• an example of a divisor not having the property, and
• an algorithm to compute the V-filtration along a divisor up to a given order.

     

A comparison of lower bounds for the symmetric circulant traveling salesman problem

When the matrix of distances between cities is symmetric and circulant, the traveling salesman problem (TSP) reduces to the so-called symmetric circulant traveling salesman problem (SCTSP), that has applications in the design of reconfigurable networks, and in minimizing wallpaper waste. The complexity of the SCTSP is open, but conjectured to be NP-hard, and we compare different lower bounds on the optimal value that may be computed in polynomial time. We derive a new linear programming (LP) relaxation of the SCTSP from the semidefinite programming (SDP) relaxation in [E. de Klerk, D.V. Pasechnik, R. Sotirov, On semidefinite programming relaxation of the traveling salesman problem, SIAM Journal of Optimization 19 (4) (2008) 1559-1573]. Further, we discuss theoretical and empirical comparisons between this new bound and three well-known bounds from the literature, namely the Held-Karp bound [M. Held, R.M. Karp, The traveling salesman problem and minimum spanning trees, Operations Research 18 (1970) 1138-1162], the 1-tree bound, and the closed-form bound for SCTSP proposed in [J.A.A. van der Veen, Solvable cases of TSP with various objective functions, Ph.D. Thesis, Groningen University, The Netherlands, 1992].     

A new class of cutting planes for the symmetric travelling salesman problem

A comprehensive class of cutting planes for the symmetric travelling salesman problem (TSP) is proposed which contains the known comb inequalities, the path inequalities and the 3-star constraints as special cases. Its relation to the clique tree inequalities is discussed. The cutting planes are shown to be valid for a relaxed version of the TSP, the travelling salesman problem on a road network, and—under certain conditions—to define facets of the polyhedron associated with this problem.     

Efficient local search algorithms for known and new neighborhoods for the generalized traveling salesman problem

The generalized traveling salesman problem (GTSP) is a well-known combinatorial optimization problem with a host of applications. It is an extension of the Traveling Salesman Problem (TSP) where the set of cities is partitioned into so-called clusters, and the salesman has to visit every cluster exactly once.     

Recognition by spectrum for finite simple groups of Lie type

The goal of this article is to survey new results on the recognition problem. We focus our attention on the methods recently developed in this area. In each section, we formulate related open problems. In the last two sections, we review arithmetical characterization of spectra of finite simple groups and conclude with a list of groups for which the recognition problem was solved within the last three years.      

A New Memetic Algorithm for the Asymmetric Traveling Salesman Problem

This paper introduces a new memetic algorithm specialized for the asymmetric instances of the traveling salesman problem (ATSP). The method incorporates a new local search engine and many other features that contribute to its effectiveness, such as: (i) the topological organization of the population as a complete ternary tree with thirteen nodes; (ii) the hierarchical organization of the population in overlapping clusters leading to the special selection scheme; (iii) efficient data structures. Computational experiments are conducted on all ATSP instances available in the TSPLIB, and on a set of larger asymmetric instances with known optimal solutions. The comparisons show that the results obtained by our method compare favorably with those obtained by several other algorithms recently proposed for the ATSP.     

A criterion for subnormality of subgroups in finite groups

Based on Wielandt’s criterion for subnormality of subgroups in finite groups, we study 2-maximal subgroups of finite groups and present another subnormality criterion in finite solvable groups.     

A quadratically convergent local algorithm on minimizing sums of the largest eigenvalues of a symmetric matrix

In this paper, we consider the problem on minimizing sums of the largest eigenvalues of a symmetric matrix which depends on the decision variable affinely. An important application of this problem is the graph partitioning problem, which arises in layout of circuit boards, computer logic partitioning, and paging of computer programs. Given 0, we first derive an optimality condition which ensures that the objective function is within error bound of the solution. This condition may be used as a practical stopping criterion for any algorithm solving the underlying problem. We also show that, in a neighborhood of the minimizer, the optimization problem can be equivalently formulated as a smooth constrained problem. An existing algorithm on minimizing the largest eigenvalue of a symmetric matrix is shown to be applicable here. This algoritm enjoys the property that if started close enough to the minimizer, then it will converge quadratically. To implement a practical algorithm, one needs to incorporate some technique to generate a good starting point. Since the problem is convex, this can be done by using an algorithm for general convex optimization problems (e.g., Kelley's cutting plane method or ellipsoid methods), or an algorithm specific for the optimization problem under consideration (e.g., the algorithm developed by Cullum, Donath, and Wolfe). Such union ensures that the overall algorithm has global convergence with quadratic rate. Finally, the results presented in this paper are readily extended on minimizing sums of the largest eigenvalues of a Hermitian matrix.Some of results in this paper were given in [19] without proofs.