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Akartunal K.,University of Strathclyde | Boland N.,University of Newcastle | Evans I.,Constraint Technologies International | Wallace M.,Monash University | And 2 more authors.
Computers and Operations Research | Year: 2013

This paper is the first of two papers entitled Airline Planning Benchmark Problems, aimed at developing benchmark data that can be used to stimulate innovation in airline planning, in particular, in flight schedule design and fleet assignment. While optimisation has made an enormous contribution to airline planning in general, the area suffers from a lack of standardised data and benchmark problems. Current research typically tackles problems unique to a given carrier, with associated specification and data unavailable to the broader research community. This limits direct comparison of alternative approaches, and creates barriers of entry for the research community. Furthermore, flight schedule design has, to date, been under-represented in the optimisation literature, due in part to the difficulty of obtaining data that adequately reflects passenger choice, and hence schedule revenue. This is Part I of two papers taking first steps to address these issues. It does so by providing a framework and methodology for generating realistic airline demand data, controlled by scalable parameters. First, a characterisation of flight network topologies and network capacity distributions is deduced, based on the analysis of airline data. Then a multi-objective optimisation model is proposed to solve the inverse problem of inferring OD-pair demands from passenger loads on arcs. These two elements are combined to yield a methodology for generating realistic flight network topologies and OD-pair demand data, according to specified parameters. This methodology is used to produce 33 benchmark instances exhibiting a range of characteristics. Part II extends this work by partitioning the demand in each market (OD pair) into market segments, each with its own utility function and set of preferences for alternative airline products. The resulting demand data will better reflect recent empirical research on passenger preference, and is expected to facilitate passenger choice modelling in flight schedule optimisation. © 2012 Elsevier Ltd. Source


Akartunal K.,University of Strathclyde | Akartunal K.,University of Melbourne | Boland N.,University of Newcastle | Boland N.,University of Melbourne | And 4 more authors.
Computers and Operations Research | Year: 2013

This paper is the second of two papers entitled Airline Planning Benchmark Problems, aimed at developing benchmark data that can be used to stimulate innovation in airline planning, in particular, in flight schedule design and fleet assignment. The former has, to date, been under-represented in the optimisation literature, due in part to the difficulty of obtaining data that adequately reflects passenger choice, and hence schedule revenue. Revenue models in airline planning optimisation only roughly approximate the passenger decision process. However, there is a growing body of literature giving empirical insights into airline passenger choice. Here we propose a new paradigm for passenger modelling, that enriches our representation of passenger revenue, in a form designed to be useful for optimisation. We divide the market demand into market segments, or passenger groups, according to characteristics that differentiate behaviour in terms of airline product selection. Each passenger group has an origin, destination, size (number of passengers), departure time window, and departure time utility curve, indicating willingness to pay for departure in time sub-windows. Taking as input market demand for each origin-destination pair, we describe a process by which we construct realistic passenger group data, based on the analysis of empirical airline data collected by our industry partner. We give the results of that analysis, and describe 33 benchmark instances produced. © 2012 Elsevier Ltd. Source


Wazny J.,Constraint Technologies International
Journal of Functional Programming | Year: 2010

C-Rules is a business rules management system developed by Constraint Technologies International (www.constrainttechnologies.com) that is designed for use in transport, travel and logistics problems. Individual businesses within these industries often need to solve the same kinds of problems related to scheduling of operations, resource allocation, staff rostering and so on, but each organisation has its own rules and procedures. Furthermore, these problems tend to be combinatorially challenging: before a final solution is chosen, many potential choices need to be generated, evaluated and compared. In C-Rules, users define rules that describe various aspects of a problem. These rules can be invoked from an application, which is typically either an optimising solver or an interactive planning tool. Rules can be used to encode evaluation criteria, such as the legality or cost of a proposed solution, or values like configuration parameters that may be used by the host application to tune or direct its progress. At its core, C-Rules provides a functional expression language that affords users power and flexibility when formulating rules. In this paper we will describe our experiences of using functional programming both at the end-user level and at the implementation level. We highlight some of the benefits of basing our rule system on features such as higher-order functions, referential transparency and static, polymorphic typing. We also outline some of our experiences in using Haskell to build an efficient compiler for the core language. © 2010 Cambridge University Press. Source


Boland N.,University of Newcastle | Engineer F.,University of Newcastle | Evans I.,Constraint Technologies International | Ruther S.,University of Newcastle
51st AGIFORS Annual Proceedings - Annual Symposium and Study Group Meeting, AGIFORS 2011 | Year: 2011

Still work in progress. Challenge: large number of pricing problems. Gain flexibility by delaying scheduling decisions until 4 days before day of operations. Generates routes while considering the actual tail number and actual maintenance. Large number of pricing problems. Copyright © (2011) by AGIFORS. Source


Bolan N.,University of Newcastle | Evans I.,Constraint Technologies International | Mears C.,Monash University | Niven T.,Monash University | And 3 more authors.
WIT Transactions on the Built Environment | Year: 2012

In a suburban passenger railway network, a delay of a single train is likely to affect not only the passengers aboard or waiting for that train, but those on subsequent trains as well. These knock-on effects are caused by the delayed train blocking sections of track and lead to congestion and slower boarding rate on overcrowded trains. When a delay has occurred, the delayed trains and other nearby trains can be re-scheduled to minimise the detrimental effect of the delay. This paper shows how to re-schedule to minimize negative impact on passengers. A simple double track train network with a single delay is considered. The model takes into account the travel times of passengers, boarding times at stations which are lengthened when the train is crowded, and the ability of trains to bypass stations. © 2012 WIT Press. Source

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