Vehicle routing and crew scheduling for metropolitan mail distribution at Australia Post

This paper presents a new multi-depot combined vehicle and crew scheduling algorithm, and uses it, in conjunction with a heuristic vehicle routing algorithm, to solve the intra-city mail distribution problem faced by Australia Post. First we describe the Australia Post mail distribution problem and outline the heuristic vehicle routing algorithm used to find vehicle routes. We present a new multi-depot combined vehicle and crew scheduling algorithm based on set covering with column generation. The paper concludes with a computational investigation examining the affect of different types of vehicle routing solutions on the vehicle and crew scheduling solution, comparing the different levels of integration possible with the new vehicle and crew scheduling algorithm and comparing the results of sequential versus simultaneous vehicle and crew scheduling, using real life data for Australia Post distribution networks.

The Populist Message of Australian Country Music

Australian country music is influenced by American country music and Australian bush ballads. This music idealises genuine true blue inhabitants of an idealised rural heartland and fuses nationalism with agrarian mythology. The lyrics of a number of country songs contain a populist political message, which is frequently nationalistic but is a form of nationalism.

Incremental learning for interactive e-mail filtering

In this article, we propose a framework, namely, Prediction-Learning-Distillation (PLD) for interactive document classification and distilling misclassified documents. Whenever a user points out misclassified documents, the PLD learns from the mistakes and identifies the same mistakes from all other classified documents. The PLD then enforces this learning for future classifications. If the classifier fails to accept relevant documents or reject irrelevant documents on certain categories, then PLD will assign those documents as new positive/negative training instances. The classifier can then strengthen its weakness by learning from these new training instances. Our experiments’ results have demonstrated that the proposed algorithm can learn from user-identified misclassified documents, and then distil the rest successfully.

An analysis of the images attached to referral messages in an e-mail based telemedicine system for developing countries

Little is known about the quality of the images transmitted in email telemedicine systems. The present study was designed to survey the quality of images transmitted in the Swinfen Charitable Trust email referral system. Telemedicine cases were examined for a 3 month period in 2002 and a 3 month period in 2006. The number of cases with images attached increased from 8 (38%) to 37 (53%). There were four types of images (clinical photographs, microscope pictures, notes and X-ray images) and the proportion of radiology images increased from 27 to 48%. The cases in 2002 came from four different hospitals and were associated with seven different clinical specialties. In 2006, the cases came from 19 different hospitals and 20 different specialties. The 46 cases (from both study periods) had a total of 159 attached images. The quality of the images was assessed by awarding each image a score in four categories: focus, anatomical perspective, composition and lighting. The images were scored on a five-point scale (1 = very poor to 5 =very good) by a qualified medical photographer. In comparing image quality between the two study periods, there was some evidence that the quality had reduced, although the average size of the attached images had increased. The median score for all images in 2002 was 16 (interquartile range 14-19) and the median score in 2006 was 15 (13-16). The difference was significant (P < 0.001, Mann-Whitney test).

Extending the theory of Owicki and Gries with asynchronous message passing

We describe an extension of the theory of Owicki and Gries (1976) to a programming language that supports asynchronous message passing based on unconditional send actions and conditional receive actions. The focus is on exploring the fitness of the extension for distributed program derivation. A number of experiments are reported, based on a running example problem, and with the aim of exploring design heuristics and of streamlining derivations and progress arguments.

Design and implementation of an automatic message-routing system for low-cost telemedicine

Email has been used for some years as a low-cost telemedicine medium to provide support for developing countries. However, all operations have been relatively small scale and fairly labour intensive to administer. A scalable, automatic message-routing system was constructed which automates many of the tasks. During a four-month study period in 2002, 485 messages were processed automatically. There were 31 referrals from eight hospitals in three countries. These referrals were handled by 25 volunteer specialists from a panel of 42. Two system operators, located 10 time zones apart, managed the system. The median time from receipt of a new referral to its allocation to a specialist was 1.0 days (interquartile range 0.7-2.4). The median interval between allocation and first reply was 0.7 days (interquartile range 0.3-2.3). Automatic message handling solves many of the problems of manual email telemedicine systems and represents a potentially scalable way of doing low-cost telemedicine in the developing world.

Improved message passing for inference in densely connected systems

An improved inference method for densely connected systems is presented. The approach is based on passing condensed messages between variables, representing macroscopic averages of microscopic messages. We extend previous work that showed promising results in cases where the solution space is contiguous to cases where fragmentation occurs. We apply the method to the signal detection problem of Code Division Multiple Access (CDMA) for demonstrating its potential. A highly efficient practical algorithm is also derived on the basis of insight gained from the analysis. © EDP Sciences.

Message passing for task redistribution on sparse graphs

The problem of resource allocation in sparse graphs with real variables is studied using methods of statistical physics. An efficient distributed algorithm is devised on the basis of insight gained from the analysis and is examined using numerical simulations, showing excellent performance and full agreement with the theoretical results.

Genetics and competing strategies in a threshold model for mail processing

Multi-agent algorithms inspired by the division of labour in social insects are applied to a problem of distributed mail retrieval in which agents must visit mail producing cities and choose between mail types under certain constraints.The efficiency (i.e. the average amount of mail retrieved per time step), and the flexibility (i.e. the capability of the agents to react to changes in the environment) are investigated both in static and dynamic environments. New rules for mail selection and specialisation are introduced and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a genetic algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation. From a more theoretical point of view, in order to avoid finite size effects, most results are obtained for large population sizes. However, we do analyse the influence of population size on the performance. Furthermore, we critically analyse the causes of efficiency loss, derive the exact dynamics of the model in the large system limit under certain conditions, derive theoretical upper bounds for the efficiency, and compare these with the experimental results.

Majority versus minority influence, message processing and attitude change:the Source-Context-Elaboration Model

This chapter examines the contexts in which people will process more deeply, and therefore be more influenced by, a position that is supported by either a numerical majority or minority. The chapter reviews the major theories of majority and minority influence with reference to which source condition is associated with most message processing (and where relevant, the contexts under which this occurs) and experimental research examining these predictions. The chapter then presents a new theoretical model (the source-context-elaboration model, SCEM) that aims to integrate the disparate research findings. The model specifies the processes underlying majority and minority influence, the contexts under which these processes occur and the consequences for attitudes changed by majority and minority influence. The chapter then describes a series of experiments that address each of the aspects of the theoretical model. Finally, a range of research-related issues are discussed and future issues for the research area as a whole are considered.

Majority versus minority influence:the role of message processing in determining resistance to counter-persuasion

Two experiments examined the extent to which attitudes changed following majority and minority influence are resistant to counter-persuasion. In both experiments participants' attitudes were measured after being exposed to two messages, delayed in time, which argued opposite positions (initial message and counter-message). In the first experiment, attitudes following minority endorsement of the initial message were more resistant to a second counter-message only when the initial message contained strong versus weak arguments. Attitudes changed following majority influence did not resist the second counter-message and returned to their pre-test level. Experiment 2 varied whether memory was warned (i.e., message recipients expected to recall the message) or not, to manipulate message processing. When memory was warned, which should increase message processing, attitudes changed following both majority and minority influence resisted the second counter-message. The results support the view that minority influence instigates systematic processing of its arguments, leading to attitudes that resist counter-persuasion. Attitudes formed following majority influence yield to counter-persuasion unless there is a secondary task that encourages message processing.

Effects of caffeine on persuasion and attitude change:the role of secondary tasks in manipulating systematic message processing

Two experiments are reported that examine the effects of caffeine consumption on attitude change by using different secondary tasks to manipulate message processing. The first experiment employed an orientating task whilst the second experiment employed a distracter task. In both experiments participants consumed an orange-juice drink that either contained caffeine (3.5?mg/kg body weight) or did not contain caffeine (placebo) prior to reading a counter-attitudinal communication. The results across both experiments were similar. When message processing was reduced or under high distraction, there was no attitude change irrespective of caffeine consumption. However, when message processing was enhanced or under low distraction, there was greater attitude change in the caffeine vs. placebo conditions. Furthermore, attitudes formed after caffeine consumption resisted counter-persuasion (Experiment 1) and led to indirect attitude change (Experiment 2). The extent that participants engaged in message-congruent thinking mediated the amount of attitude change. These results provide evidence that moderate amounts of caffeine increase systematic processing of the arguments in the message resulting in greater agreement.