The Transit Route Arc-Node Service Maximization problem

This article presents a new method for determining optimal transit routes. The Transit Route Arc-Node Service Maximization model is a mathematical model that maximizes the service value of a route, rather than minimizing cost. Cost (distance) is considered as a budget constraint on the extent of the route. The mathematical formulation modifies and exploits the structure of linear programming problems designed for the traveling salesman problem. An innovative divide-and-conquer solution procedure is presented that not only makes the transit routing problem tractable, but also provides a range of high-quality alternate routes for consideration, some of which have substantially varying geometries. Variant formulations are provided for several common transit route types. The model is tested through its application to an existing street network in Richardson, TX. Optimal numeric results are obtained for several problem instances, and these results demonstrate that increased route cost is not correlated with increased service provision.     

Z(2) gauge neural network and its phase structure

We study general phase structures of neural-network models that have Z(2) local gauge symmetry. The Z(2) spin variable _Si=±1$S_i=\pm 1$ on the i$i$-th site describes a neuron state as in the Hopfield model, and the Z(2) gauge variable _Jij=±1$J_{ij}=\pm 1$ describes a state of the synaptic connection between j$j$-th and i$i$-th neurons. The gauge symmetry allows for a self-coupling energy among _Jij$J_{ij}$’s such as _JijJjkJki$J_{ij}{J}_{jk}{J}_{ki}$, which describes reverberation of signals. Explicitly, we consider the three models; (I) an annealed model with full and partial connections of _Jij$J_{ij}$, (II) a quenched model with full connections where _Jij$J_{ij}$ is treated as a slow quenched variable, and (III) a quenched three-dimensional lattice model with the nearest-neighbor connections. By numerical simulations, we examine their phase structures paying attention to the effect of the reverberation term, and compare them with each other and with the annealed 3D lattice model which has been studied beforehand. By noting the dependence of thermodynamic quantities upon the total number of sites and the connectivity among sites, we obtain a coherent interpretation to understand these results. Among other things, we find that the Higgs phase of the annealed model is separated into two stable spin-glass phases in the quenched models (II) and (III).     

A novel algorithm to integrate synchronous digital hierarchy networks into Optical Transport Network using mixed line rates

In this era of high data transfer speeds and new age technologies, Optical Transport Network (OTN) along with its newly introduced Optical Transport Hierarchy (OTH) has provided a lease of life to legacy low rate networks. It has provided a common backbone for multiple data rates to coexist on same fiber along with the enhanced transmission reach. The cost effective Optical Transport Network design has always been a complex issue due to the presence of multiple variables like number of fibers on each link, available data rates on each fiber, the wavelength count, transmission reach at each data rate, etc. In this paper an Integer Linear Programming (ILP) model has been presented to solve Routing problem for Synchronous Digital Hierarchy (SDH) over OTN over DWDM design. Optical Transport Hierarchy (OTH) has been used to integrate heterogenous SDH/SONET operating at different rates (STM-16, STM-64 and STM-256) into a single network supporting mixed line rates. These rates can coexist in a same fiber but each rate carries different cost with it. The objective function aims at finding the least cost routing solution by looking at different tradeoffs between the Capital Expenditure and the operational expenditure. Certainly different variables like the number of fibers and wavelengths, transmission reach, etc. are a factor in it. A mechanism has been put to monitor the Bit Error Rate (BER) levels as well. For evaluating the ILP model, 18 Node 38 Link European Optical Network was considered as the reference model and two ordering techniques, namely, full ILP and highest rate first (HRF) were used for deriving the results. The ILP model was designed with minimum of decision variables so in spite of big reference network it converges much faster. Under the given conditions, full ILP gave least cost network whereas HRF ordering took least time for ILP to converge.     

Fast deterministic approximation for the multicommodity flow problem

In this paper we consider an optimization version of the multicommodity flow problem which is known as the maximum concurrent flow problem. We show that an approximate solution to this problem can be computed deterministically using O(k(ε ⁻² + logk) logn) 1-commodity minimum-cost flow computations, wherek is the number of commodities,n is the number of nodes, andε is the desired precision. We obtain this bound by proving that in the randomized algorithm developed by Leighton et al. (1995) the random selection of commodities can be replaced by the deterministic round-robin without increasing the total running time. Our bound significantly improves the previously known deterministic upper bounds and matches the best known randomized upper bound for the approximation concurrent flow problem. A preliminary version of this paper appeared inProceedings of the 6th ACM-SIAM Symposium on Discrete Algorithms, San Francisco CA, 1995, pp. 486–492.     

贷款分配方法的数学模型及其解法

为了解决三角债问题，银行给出一笔贷款，应该如何分配这笔贷款，使清理的债务达到最大。本文建立这个问题的数学模型，并且给出一个解法。     

Computational aspects of two-segment separable programming

Recursive separable programming algorithms based on local, two-segment approximations are described for the solution of separable convex programs. Details are also given for the computation of lower bounds on the optimal value by both a primal and a dual approach, and these approaches are compared. Computational comparisons of the methods are provided for a variety of test problems, including a water supply application (with more than 600 constraints and more than 900 variables) and an econometric modelling problem (with more than 200 variables). Research supported by National Science Foundation Grants MCS74-20584 A02 and MCS-7901066.     

The network approach to calculation of characteristic time constants of the flat two-layer superconducting cable

The matrix method was used to investigate the process of current decay in the samples of flat two-layer superconducting cables. The discrete spectrum of eigen-frequencies has been obtained. Each of these frequencies determines the rate of decay of the correspondent eigen-current. Despite of the increasing of the number of eigen-frequencies with the enlargement of the sample dimensions the spectrum remains finite, as the maximum and minimum frequencies tend to finite limits. An analysis made for the lowest eigen-frequencies showed the corresponding eigen-currents to be slowly decaying long current loops. Within the range of high frequencies the sinusoidal distribution of eigen-currents in the rows of the cable was observed.     

Spin-orbit scattering in the quantum Hall effect

We study dynamics of electrons in a magnetic field using a network model with two channels per link with random mixing, while the intrachannel potential is periodic (non-random); the channels represent two spin states. We consider channel mixing as function of the energy separation of the two extended states, and show that the phase diagram is different from the standard quantum Hall diagram for random intrachannel potential.     

A new method for characterizing patterns of neural spike trains and its application

A method for characterizing and identifying firing patterns of neural spike trains is presented. Based on the time evolution of a neural spike train, the counting process is constructed as a time-dependent stair-like function. Three characteristic variables defined at sequential moments, including two formal derivatives and the integration of the counting process, are introduced to reflect the temporal patterns of a spike train. The reconstruction of a spike train with these variables verify the validity of this method. And a model of cold receptor is used as an example to investigate the temporal patterns under different temperature conditions. The most important contribution of our method is that it not only can reflect the features of spike train patterns clearly by using their geometrical properties, but also it can reflect the trait of time, especially the change of bursting of spike train. So it is a useful complementarity to conventional method of averaging.