Decision Engineering Report (DEG) Series
Permanent URI for this collection
The 'Decision Engineering Report Series' from Cranfield University publishes the research results from the Centre for Decision Engineering in Enterprise Integration. The research centre aims to establish itself as the leader in applied decision engineering research. The group's client base includes: Airbus, BAE SYSTEMS, BOC Edwards, BT Exact, Corus, EDS (Electronic Data Systems), Ford Motor Company, GKN Aerospace, Ministry of Defence (UK MOD), Nissan Technology Centre Europe, Johnson Controls, PRICE Systems, Rolls-Royce, Society of Motor Manufacturers and Traders (SMMT) and XR Associates. The intention of the report series is to disseminate the centre’s findings faster and with greater detail than regular publications. The reports are produced on the core research interests within the centre:
Joshua Knowles,
University of Manchester
Erel Avineri,
University of the West of England
Keshav Dahal,
University of Bradford
Ashraf Saad,
Georgia Tech, USA
Muhammad Sarfraz,
King Fahd University of Petroleum and Minerals, Saudi Arabia
Soumya Banerjee,
Birla Institute of Technology, Mesra, India
Mauro Dell'Orco,
Polytechnic of Bari, Italy
Nirupam Chakraborti,
Indian Institute of Technology, Kharagpur, India
Dr Stephen O T Ogaji,
Cranfield University
Dr. Phillip Burrell,
Southbank University
Dr. Basim Majeed,
Intelligent Systems Research Group, BT Research Laboratories
Dr. Goran Bezanov,
Southbank University
Qing Wang,
Durham University
Fredrik Elgh,
Jönköping University, Sweden
Raymond P. Covert,
Technical Director, MCR, Fairfax, USA
P. M. Wognum,
University of Twente, The Netherlands
Dr Derek Ford,
University of Cambridge
Ricardo Goncalves,
Uninova, Portugal
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Cost engineering
Product engineering
Applied soft computing
Currently edited by:
Professor Rajkumar Roy and Yuchun Xu
r.roy@cranfield.ac.uk
yuchun.xu@cranfield.ac.uk
Manufacturing Department
Cranfield University
Cranfield
Bedfordshire
MK43 OAL
International Review Panel:
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International Panel members:
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Recent Submissions
Item Open Access Grid computing for engineering design optimisation: Evolution and future trends(2007-03-01T00:00:00Z) Goteng, Gokop; Tiwari, Ashutosh; Roy, Rajkumar; EditorGrid Computing is fast gaining ground both within academia and the commercial sectors. It has shifted from its traditional scientific-based applications to serviceoriented problem solving environments for commerce and business. Engineering design optimisation (EDO) is characteristically computationally and data intensive. EDO is also a multidisciplinary field which requires the collaboration of different domain experts to work on a design to yield improved versions. Grid Computing offers a suitable platform for design engineers to collaboratively work together and share knowledge and expertise in addition to the computational and data facility that can be combined to bear on complex designs. In this paper, the trend of Grid Computing evolution shows a clear emergence of application areas, starting from computational grid, data grid, visualisation grid and semantic grid to service-oriented problem solving environments (SO-PSE). This evolution is classified as first, second and third generation of Grid Computing for the purpose of understanding how researchers have tried to provide solutions to the problems and challenges in implementing Grid applications. The future of Grid Computing research areas such as autonomic computing, ubiquitous computing and economic Grid models as well as concurrent engineering design problem solving environments feature in the report. Autonomic computing enables grid services and resources to have self-management, self adjustable and adaptability to changing and dynamic situations using agent-based technology while ubiquitous computing allows computers to perceive the environment and act accordingly.Item Open Access Challenges in real world optimisation using evolutionary computing(2004-11-10T00:00:00Z) Tiwari, Ashutosh; Roy, RajkumarChallenges in real world optimisation using evolutionary computing With rising global competition, it is becoming increasingly more important for industry to optimise its activities. However, the complexity of real-life optimisation problems has prevented industry from exploiting the potential of optimisation algorithms. Industry has therefore relied on either trial-and-error or over- simplification for dealing with its optimisation problems. This has led to the loss of opportunity for improving performance, saving costs and time. The growth of research in the field of evolutionary computing has been encouraged by a desire to harness this opportunity. There are a number of benefits of evolutionary-based optimisation that justify the effort invested in this area. The most significant advantage lies in the gain of flexibility and adaptability to the task in hand, in combination with robust performance and global search characteristics. This report presents the proceedings of the workshop on ‘Challenges in Real World Optimisation Using Evolutionary Computing’. This workshop is organised in association with the Eighth International Conference on Parallel Problem Solving from Nature (PPSN VIII) held in Birmingham (UK) on 18- 22 September 2004. The aim of this workshop is to explore the use of evolutionary computing techniques for solving real-life optimisation problems. It is the purpose of this workshop to bring together researchers working in the area of industrial application of evolutionary-based computing techniques such as genetic algorithms, evolutionary programming, genetic programming and evolutionary strategies. The workshop provides a great opportunity for presenting and disseminating latest work in optimisation applications of evolutionary computing in varied industry sectors and application areas, e.g. manufacturing, service, bioinformatics and retail. It provides a forum for identifying and exploring the key issues that affect the industrial application of evolutionary-based computing techniques. This report presents three papers from the workshop. The first paper examines the possibilities of train running time control using genetic algorithms for the minimisation of energy costs in DC rapid transit systems. The second paper provides an overview of soft computing techniques used in the lead identification and optimisation stages of the drug discovery process. The third paper proposes a micro-evolutionary programming technique for optimisation of continuousItem Open Access Technology selection for human behaviour modelling in contact centres(2006-01-01T00:00:00Z) Shah, Satya Ramesh; Roy, Rajkumar; Tiwari, Ashutosh; EditorCustomer service advisors can play different roles and have different level of autonomy, but at the end they are humans with heart and voice. While product purchases, lifestyle information and billing data provide important information about customers, it is call detail records that describe a customer’s behaviour and define their satisfaction with the services offered. Call detail records describe the transactions between customer and the company. This study looks on different techniques that can be used to model customer and CSA (customer service advisor) behaviour within a contact centre environment. A brief overview of the contact centre environment is discussed focusing on issues of customer and service advisor and the need to categorise customer and advisor within contact centre environment. The findings from the case study analysis within the current contact centres, provides the authors with understanding of different behaviour observed for customer and CSA’s within contact centres. The study also examines different human behaviour modelling techniques which the authors are interested in using to develop a model which can categorise the human with respect to demographic, experience and behavioural attributes within the context. Through the study it can be seen that soft computing techniques provide a major role in modelling of human behaviour and thus providing better results where this technique can be applied. The authors have also carried out a comparative analysis of all the techniques discussed within the paper and as seen from the analysis that soft computing techniques are widely used to model the user/human behaviour and thus can provide a platform for future research. Soft computing represents a significant paradigm shift in the aim of computing, a shift that reflects the fact that the human mind, unlike state of the art computers, possesses a remarkable ability to store and process information, which is pervasively imprecise, uncertain, and lacking in categoricItem Open Access A methodology for the selection of new technologies in the aviation industry(2004-11-29T00:00:00Z) Houseman, Oliver; Tiwari, Ashutosh; Roy, Rajkumar; EditorThe purpose of this report is to present a technology selection methodology to quantify both tangible and intangible benefits of certain technology alternatives within a fuzzy environment. Specifically, it describes an application of the theory of fuzzy sets to hierarchical structural analysis and economic evaluations for utilisation in the industry. The report proposes a complete methodology to accurately select new technologies. A computer based prototype model has been developed to handle the more complex fuzzy calculations. Decision-makers are only required to express their opinions on comparative importance of various factors in linguistic terms rather than exact numerical values. These linguistic variable scales, such as ‘very high’, ‘high’, ‘medium’, ‘low’ and ‘very low’, are then converted into fuzzy numbers, since it becomes more meaningful to quantify a subjective measurement into a range rather than in an exact value. By aggregating the hierarchy, the preferential weight of each alternative technology is found, which is called fuzzy appropriate index. The fuzzy appropriate indices of different technologies are then ranked and preferential ranking orders of technologies are found. From the economic evaluation perspective, a fuzzy cash flow analysis is employed. This deals quantitatively with imprecision or uncertainties, as the cash flows are modelled as triangular fuzzy numbers which represent ‘the most likely possible value’, ‘the most pessimistic value’ and ‘the most optimistic value’. By using this methodology, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision- making process when selecting new technologies in which to invest. The prototype model was validated with a case study within the aviation industry that ensured it was properly configured to meet the industry's specific requirements.Item Open Access Cost engineering: why, what and how?(2003-09-18T00:00:00Z) Roy, Rajkumar; EditorCost has become a major business driver in many industries. It is observed that there is a lack of understanding about the process to estimate, manage and control costs across the lifecycle of a product. This report presents a business case to understand the principles of ‘Cost Engineering’ within the manufacturing industries. The main focus of the report is in the techniques and tools used in cost estimating – one of the major activities in cost engineering. Five different methods of cost estimating are discussed in the report along with cost management issues including risk analysis. The report also presents research findings on ‘industry practice’ in hardware and software development cost estimating. The study shows the lack of research in hardware cost estimating and highlights the lack of communication within different groups of people involved in cost engineering. The report then focuses on the research trends in cost engineering and presents two case studies from recent research projects at Cranfield University. The case studies clearly show the progress in formalising the cost engineering process and the improvements in the current understanding about the domain. Two major areas of research as identified in the report are: i) integrating the cost engineering capability with the ERP (enterprise resource planning) environment so that data can be shared effectively, and ii) capture and reuse of human expertise in cost engineering for performance improvement. Finally, the report also identifies the need for simpler and cheaper cost engineering software for Small and Medium scale EnterprisItem Open Access Text classification method review(2007-04-01T00:00:00Z) Mahinovs, Aigars; Tiwari, Ashutosh; Roy, Rajkumar; Baxter, DavidWith the explosion of information fuelled by the growth of the World Wide Web it is no longer feasible for a human observer to understand all the data coming in or even classify it into categories. With this growth of information and simultaneous growth of available computing power automatic classification of data, particularly textual data, gains increasingly high importance. This paper provides a review of generic text classification process, phases of that process and methods being used at each phase. Examples from web page classification and spam classification are provided throughout the text. Principles of operation of four main text classification engines are described – Naïve Bayesian, k Nearest Neighbours, Support Vector Machines and Perceptron Neural Networks. This paper will look through the state of the art in all these phases, take note of methods and algorithms used and of different ways that researchers are trying to reduce computational complexity and improve the precision of text classification process as well as how the text classification is used in practice. The paper is written in a way to avoid extensive use of mathematical formulae in order to be more suited for readers with little or no background in theoretical mathematiItem Open Access Handling integrated quantitative and qualitative search space in engineering design optimisation problems(2003-09-18T00:00:00Z) Oduguwa, Victor; Tiwari, Ashutosh; Roy, Rajkumar; EditorSince information in engineering design problems can be both quantitative (QT) and qualitative (QL) in nature, combining both types of information can result in more realistic solutions for real world optimisation problems. However, most of the approaches reported in the literature are incapable of conducting optimisation searches in such a mixed environment. Therefore this report proposes a mathematically proven methodology for handling integrated QT and QL search space in real world optimisation problems. The report begins by presenting the definition of these optimisation problems, an analysis of the challenges that they pose for existing optimisation strategies and related research. The report then presents the proposed solution strategy and the mathematical proof. Furthermore, a case study on a rod rolling problem is presented to validate the effectiveness of the proposed methodology. The report concludes with a brief outline of limitations and future research activities.Item Open Access An Ontology for Product-Service Systems(Cranfield University, 2010) Annamalai Vasantha, Gokula Vijaykumar; Hussain, Romana; Cakkol, Mehmet; Roy, Rajkumar; Evans, Stephen; Tiwari, Ashutosh; Xu, YuchunIndustries are transforming their business strategy from a product-centric to a more service-centric nature by bundling products and services into integrated solutions to enhance the relationship between their customers. Since Product- Service Systems design research is currently at a rudimentary stage, the development of a robust ontology for this area would be helpful. The advantages of a standardized ontology are that it could help researchers and practitioners to communicate their views without ambiguity and thus encourage the conception and implementation of useful methods and tools. In this paper, an initial structure of a PSS ontology from the design perspective is proposed and evaluated.