Browsing by Author "Majeed, Basim"
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Item Open Access Business process improvement using multi-objective optimisation(Springer Verlag, 2006) Vergidis, K.; Tiwari, Ashutosh; Majeed, BasimBusiness process redesign and improvement has become an increasingly attractive subject in the wider area of business process intelligence. Although there have been many attempts to establish a business process redesign framework, there is little work on the actual optimisation of business processes with given objectives. Furthermore, most of the attempts to optimise a business process are manual and do not involve a formal automated methodology. This paper proposes a process improvement approach for automated multi-objective optimisation of business processes. The proposed framework uses a generic business process model that is formally defined. The formal definition of business processes is necessary to ensure that the optimisation will take place in a clearly defined, repeatable and verifiable way. Multi-objectivity is expressed in terms of process cost and duration as two key objectives for any business process. The business process model is programmed and incorporated into a software optimisation platform where a selection of multi-objective optimisation algorithms can be applied to a business process design. This paper outlines a case study of business process design that is optimised by the state-of-the-art multi-objective optimisation algorithm NSGA2. The results indicate that, although business process optimisation is a highly constrained problem with fragmented search space, a number of alternative optimised business processes that meet the optimisation criteria can be produced. The paper also provides directions for future research in this area.Item Open Access Customised customer support using a soft computing approach(2005-11-01T00:00:00Z) Shah, Satya Ramesh; Roy, Rajkumar; Tiwari, Ashutosh; Majeed, BasimThis paper describes the research and development of a methodology to identify the type of information required by the service advisor (CSA) within customer contact centre (CCC) environment. Data was collected through case studies carried out within five customer contact centres to derive the categories for customers and advisors based on demographic, experience, business value and behavioural attributes. We provide the methodology to develop a fuzzy expert system which assigns a new customer or advisor to the predefined categories. The authors have explained the steps which were followed for the development of the fuzzy expert system. A prototype system has been designed and developed to identify the type of customer and CSA based on the demographic, experience and behavioural attributes. The authors illustrate analysis with real data, based on the work with large scale customer contact centres. Validation of the information requirement model was carried out at the contact centres.Item Open Access Optimisation of business process designs: An algorithmic approach with multiple objectives.(Elsevier, 2007-09) Vergidis, K.; Tiwari, Ashutosh; Majeed, Basim; Roy, RajkumarMost of the current attempts for business process optimisation are manual without involving any formal automated methodology. This paper proposes a framework for multi-objective optimisation of business process designs. The framework uses a generic business process model that is formally defined and specifies process cost and duration as objective functions. The business process model is programmed and incorporated into a software platform where a selection of multi-objective optimisation algorithms is applied to a range of test designs including a real example. The test business process designs are of varying complexity and are optimised with three popular optimisation techniques (Non-Dominated Sorting Genetic Algorithm II (NSGA2), Strength Pareto Evolutionary Algorithm II (SPEA2) and Multi-Objective Particle Swarm Optimisation (MOPSO) algorithms). The results indicate that although business process optimisation is a highly constrained problem with fragmented search space; multi-objective optimisation algorithms such as NSGA2 and SPEA2 produce a satisfactory number of alternative optimised business process designs. However, the performance of the optimisation algorithms drops sharply as the complexity of the process designs increases. This paper also discusses the directions for future research in this particular area.