110 research outputs found
Efficiently solvable special cases of bottleneck travelling salesman problems
AbstractThe paper investigates bottleneck travelling salesman problems (BTSP) which can be solved in polynomial time. At first a BTSP whose cost matrix is a circulant is treated. It is shown that in the symmetric case such a BTSP can be solved in O(n log n) time. Secondly conditions are derived which guarantee that an optimal solution is a pyramidal tour. Thus this problem can be solved in O(n2) time. Finally it is shown that a BTSP with cost matrix C = (cij, where cij = aibj with a1 ≤ … ≤ an and b1 ≥ … ≥ bn can be solved in O(n2) time
On the complexity of the multiple stack TSP, kSTSP
The multiple Stack Travelling Salesman Problem, STSP, deals with the collect
and the deliverance of n commodities in two distinct cities. The two cities are
represented by means of two edge-valued graphs (G1,d2) and (G2,d2). During the
pick-up tour, the commodities are stored into a container whose rows are
subject to LIFO constraints. As a generalisation of standard TSP, the problem
obviously is NP-hard; nevertheless, one could wonder about what combinatorial
structure of STSP does the most impact its complexity: the arrangement of the
commodities into the container, or the tours themselves? The answer is not
clear. First, given a pair (T1,T2) of pick-up and delivery tours, it is
polynomial to decide whether these tours are or not compatible. Second, for a
given arrangement of the commodities into the k rows of the container, the
optimum pick-up and delivery tours w.r.t. this arrangement can be computed
within a time that is polynomial in n, but exponential in k. Finally, we
provide instances on which a tour that is optimum for one of three distances
d1, d2 or d1+d2 lead to solutions of STSP that are arbitrarily far to the
optimum STSP
The Random Quadratic Assignment Problem
Optimal assignment of classes to classrooms \cite{dickey}, design of DNA
microarrays \cite{carvalho}, cross species gene analysis \cite{kolar}, creation
of hospital layouts cite{elshafei}, and assignment of components to locations
on circuit boards \cite{steinberg} are a few of the many problems which have
been formulated as a quadratic assignment problem (QAP). Originally formulated
in 1957, the QAP is one of the most difficult of all combinatorial optimization
problems. Here, we use statistical mechanical methods to study the asymptotic
behavior of problems in which the entries of at least one of the two matrices
that specify the problem are chosen from a random distribution .
Surprisingly, this case has not been studied before using statistical methods
despite the fact that the QAP was first proposed over 50 years ago
\cite{Koopmans}. We find simple forms for and , the
costs of the minimal and maximum solutions respectively. Notable features of
our results are the symmetry of the results for and
and the dependence on only through its mean and standard deviation,
independent of the details of . After the asymptotic cost is determined for
a given QAP problem, one can straightforwardly calculate the asymptotic cost of
a QAP problem specified with a different random distribution
Minimal chordal sense of direction and circulant graphs
A sense of direction is an edge labeling on graphs that follows a globally
consistent scheme and is known to considerably reduce the complexity of several
distributed problems. In this paper, we study a particular instance of sense of
direction, called a chordal sense of direction (CSD). In special, we identify
the class of k-regular graphs that admit a CSD with exactly k labels (a minimal
CSD). We prove that connected graphs in this class are Hamiltonian and that the
class is equivalent to that of circulant graphs, presenting an efficient
(polynomial-time) way of recognizing it when the graphs' degree k is fixed
Local search heuristics for the multidimensional assignment problem
The Multidimensional Assignment Problem (MAP) (abbreviated s-AP in the case of s dimensions) is an extension of the well-known assignment problem. The most studied case of MAP is 3-AP, though the problems with larger values of s also have a large number of applications. We consider several known neighborhoods, generalize them and propose some new ones. The heuristics are evaluated both theoretically and experimentally and dominating algorithms are selected. We also demonstrate that a combination of two neighborhoods may yield a heuristics which is superior to both of its components
Single Spin Measurement using Single Electron Transistors to Probe Two Electron Systems
We present a method for measuring single spins embedded in a solid by probing
two electron systems with a single electron transistor (SET). Restrictions
imposed by the Pauli Principle on allowed two electron states mean that the
spin state of such systems has a profound impact on the orbital states
(positions) of the electrons, a parameter which SET's are extremely well suited
to measure. We focus on a particular system capable of being fabricated with
current technology: a Te double donor in Si adjacent to a Si/SiO2 interface and
lying directly beneath the SET island electrode, and we outline a measurement
strategy capable of resolving single electron and nuclear spins in this system.
We discuss the limitations of the measurement imposed by spin scattering
arising from fluctuations emanating from the SET and from lattice phonons. We
conclude that measurement of single spins, a necessary requirement for several
proposed quantum computer architectures, is feasible in Si using this strategy.Comment: 22 Pages, 8 Figures; revised version contains updated references and
small textual changes. Submitted to Phys. Rev.
Pareto Autonomous Local Search
This paper presents a study for the dynamic selection of operators in a local search process. The main purpose is to propose a generic autonomous local search method which manages operator selection from a set of available operators, built on neighborhood relations and neighbor selection functions, using the concept of Pareto dominance with respect to quality and diversity. The latter is measured using two different metrics. This control method is implemented using the Comet language in order to be easily introduced in various constraint local search algorithms. Focusing on permutation-based problems, experimental results are provided for the QAP and ATSP to assess the method’s effectiveness
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