2014 IEEE Congress on Evolutionary Computation Proceedings pages:2428-2435
2014 IEEE location:Beijing (China) date:6-11 July 2014
Organisations are constantly seeking new ways to improve operational efficiencies. This research study investigates
a novel way to identify potential efficiency gains
in business operations by observing how they are carried
out in the past and then exploring better ways of executing
them by taking into account trade-offs between time, cost and resource utilisation. This paper demonstrates how they can be incorporated in the assessment of alternative process execution scenarios by making use of a cost environment. A genetic algorithm-based approach is proposed to explore and assess alternative process execution scenarios, where the objective function is represented by a comprehensive cost structure that captures different process dimensions. Experiments conducted with different variants of the genetic algorithm evaluate the approach’s feasibility. The findings demonstrate that a genetic
algorithm-based approach is able to make use of cost reduction as a way to identify improved execution scenarios in terms of reduced case durations and increased resource utilisation. The ultimate aim is to utilise cost-related insights gained from such improved scenarios to put forward recommendations for reducing process-related cost within organisations.