Stephen Sugden

A Simulated Annealing Approach to Communication Network Design

This paper explores the use of the meta-heuristic search algorithm Simulated Annealing for solving a minimum cost network synthesis problem. This problem is a common one in the design of telecommunication networks. The formulation we use models a number of practical problems with hop-limit, degree and capacity constraints. Emphasis is placed on a new approach that uses a knapsack polytope to select amongst a number of pre-computed traffic routes in order to synthesise the network. The advantage of this approach is that a subset of the best routes can be used instead of the whole set, thereby making the process of designing large networks practicable. Using simulated annealing, we solve moderately large networks (up to 30 nodes) efficiently.

Genetic algorithms in the design of complex distribution networks

Reviews the value of network concepts as a means of portraying complex logistics and distribution systems. Reports on research which focuses on the broader issues of model formulation and solution techniques rather than specific applications. Addresses the issues of designing networks with a tree structure, and also more general ones in which loops are allowed and redundancy enforced. The decision variables involved are related to whether or not a link should exist between two specific pairs of nodes, and then what should be the level of traffic flow on that particular link. Describes the design problem in detail and possible models that could be used to represent it. Follows with a description of genetic algorithms to solve the synthesis problem of deciding the node‐link topology, and the use of linear and non‐linear programming to solve the problem of assigning traffic flow to a network with a given typology in a least‐cost manner. Concludes with a description of computational experience with solving such problems.

An integrated GA---LP approach to communication network design

In this paper we demonstrate success with an implementation of a genetic algorithm, integrated with linear programming, for solving a minimum cost network synthesis problem. The problem is formulated to include a number of practical constraints and the technique applied to moderately large networks (50 nodes). The associated linear program may be large but successful methods have been developed with very small population sizes for the genetic algorithm.

A multiservice traffic allocation model for LEO satellite communication networks

Modern telecommunication networks are characterized by a heterogeneous mix of traffic classes, ranging from traditional telephone calls to video and data services. Therefore, there is a need to solve the traffic allocation problem with different quality-of-service (QoS) requirements, wherein each traffic demand is fulfilled. This paper investigates the possibility of allocating loaded traffic in a low earth orbital (LEO) satellite network by considering multiservice traffic. Both Poisson and Markov models are used for the incoming traffic, which includes multiservice requirements. By introducing a privilege parameter, a quantum of bandwidth can be reserved for high priority traffic and a better QoS can be given for this traffic. The algorithm performs well for both traffic patterns tested. Simulation results are presented.

Applications of Spreadsheets in Education : The Amazing Power of a Simple Tool

This e-book is devoted to the use of spreadsheets in the service of education in a broad spectrum of disciplines: science, mathematics, engineering, business, and general education. The effort is aimed at collecting the works of prominent researchers and educators that make use of spreadsheets as a means to communicate concepts with high educational value. The e-book brings some of the most recent applications of spreadsheets in education and research to the fore. To offer the reader a broad overview of the diversity of applications, carefully chosen articles from engineering (power systems and control), mathematics (calculus, differential equations, and probability), science (physics and chemistry), and education are provided. Some of these applications make use of Visual Basic for Applications (VBA), a versatile computer language that further expands the functionality of spreadsheets. The material included in this e-book should inspire readers to devise their own applications and enhance their teaching and/or learning experience.

A Branch and Bound Algorithm for Capacitated Minimum Spanning Tree Problem

This paper studies the capacitated minimum spanning tree problem (CMST), which is one of the most fundamental and significant problems in the optimal design of communication networks. CMST has a great variety of applications, such as in the design of local access networks, the design of minimum cost teleprocessing networks, the vehicle routing and so on. A solution method using branch and bound technique is introduced. Computational experiences demonstrate the algorithm’s effectiveness.

A direct search approach to nonlinear integer programming

An approach to the solution of large-scale nonlinear programming problems with initeger restrictions on some of the variables is described. The method is based on the MINOS large-scale optimization algorithm and involves adjustment of the superbasic variables in integer steps. The directhsearch procedure commences from a continuous (relaxed) optimal solution and seeks the nearest integer-feasible solution in terms of objective function value. Computational experience on a wide variety of nonlinear problems is reported.

A node-oriented branch and bound algorithm for the capacitated minimum spanning tree problem

This paper studies the capacitated minimum spanning tree (CMST) problem, which is one of the most fundamental and significant problems in the optimal design of local computer networks. A solution method using a node-oriented branch and bound technique is introduced and its performance is presented. We show the advantages of the algorithm while illustrating the process of searching for the optimal solution. Techniques for finding tighter lower bounds are emphasized. Computational experiences demonstrate the algorithms effectiveness.

Construction of transmission line catenary from survey data

Abstract Precise survey data from observations of actual overhead transmission lines are commonly used to confirm theoretical predictions of sag-tension calculations, based on the standard catenary model. An algorithm is presented for determining the catenary of best fit to a set of data points in the usual cartesian coordinates. The method described employs the least-squares criterion for curve fitting, and uses the iterative Newton—Raphson algorithm to solve for the required catenary parameters. A FORTRAN 77 subroutine implementation of the algorithm is used in a conductor profile program by the South East Queensland Electricity Board, and a PC version coded in Borland Pascal is available from the author. The program uses the subroutine to generate the equation of a transmission line catenary from survey data, thus allowing rapid calculation of low-point (vertex) coordinates and conductor relative levels at arbitrary points along the span. Experimental results are presented, which indicate typical accuracy of computed conductor height to within approximately a conductor diameter.

Spreadsheets and Bulgarian goats

We consider a problem appearing in an Australian Mathematics Challenge in 2003. This article considers whether a spreadsheet might be used to model this problem, thus allowing students to explore its structure within the spreadsheet environment. It then goes on to reflect on some general principles of problem decomposition when the final goal is a successful and lucid spreadsheet implementation.