Process design optimisation using embedded hybrid visualisation and data analysis techniques within a genetic algorithm optimisation framework

Wang, K.; Salhi, Abdellah; Fraga, Eric S.

doi:10.1016/j.cep.2003.01.001

Cited by 43 publications

(12 citation statements)

References 11 publications

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“…Information on the feasible region has been proved to be beneficial even for Genetic Algorithms through the definition of specific mutation and crossover operations (Wang et al 2004).…”

Section: Introductionmentioning

confidence: 99%

Direct search of feasible region and application to a crashworthy helicopter seat

Lanzi¹,

Airoldi

Cacchione³

et al. 2011

Struct Multidisc Optim

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The paper proposes a novel approach to identify the feasible region for a constrained optimisation problem. In engineering applications the search for the feasible region turns out to be extremely useful in the understanding of the problem as the feasible region defines the portion of the domain where design parameters can be ranged to fulfil the constraints imposed on performances, manufacturing and regulations. The search for the feasible region is not a trivial task as non-convex, irregular and disjointed shapes can be found. The algorithm presented in this paper moves from the above considerations and proposes a recursive feasible-infeasible segment bisection algorithm combined with Support Vector Machine (SVM) techniques to reduce the overall computational effort. The method is discussed and then illustrated by means of three simple analytical test cases in the first part of the paper. A real-world application is finally presented: the search for the survivability L. Lanzi zone of a crashworthy helicopter seat under different crash conditions. A finite element model, including an anthropomorphic dummy, is adopted to simulate impacts that are characterised by different deceleration pulses and the proposed algorithm is used to investigate the influence of pulse shape on impact survivability.

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“…Information on the feasible region has been proved to be beneficial even for Genetic Algorithms through the definition of specific mutation and crossover operations (Wang et al 2004).…”

Section: Introductionmentioning

confidence: 99%

Direct search of feasible region and application to a crashworthy helicopter seat

Lanzi¹,

Airoldi

Cacchione³

et al. 2011

Struct Multidisc Optim

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“…Within the area of optimising business process modelling and design, Verigidis et al [30] reviewed the topics of business process modelling, analysis, and optimisation. Wang et al [32] developed an evolutionary, multi-objective …”

Section: Related Workmentioning

confidence: 99%

“…Wang et al [32] Genetic Algorithm Process Design Reduce the number of infeasible solutions generated by tailoring operators used by a genetic algorithm. Verigidis and Genetic Algorithm Process Design Generate diverse, optimised business process designs for Tiwari [29] the same process requirements.…”

Section: Related Workmentioning

confidence: 99%

Revising history for cost-informed process improvement

et al. 2015

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Organisations are constantly seeking new ways to improve operational efficiencies. This study investigates a novel way to identify potential efficiency gains in business operations by observing how they were 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 these trade-offs can be incorporated in the assessment of alternative process execution scenarios by making use of a cost environment. A number of optimisation techniques are proposed to explore and assess alternative execution scenarios. The objective function is represented by a cost structure that captures different process dimensions. An experimental evaluation is conducted to analyse the performance and scalability of the optimisation techniques: integer linear programming (ILP), hill climbing, tabu search, and our earlier proposed hybrid genetic algorithm approach. The findings demonstrate that the hybrid genetic algorithm is scalable and performs better compared to other techniques. Moreover, we argue that the use of ILP is unrealistic in this setup and cannot handle complex cost functions such as the ones we propose. Finally, we show how cost-related insights can be gained from improved execution scenarios and how these can be utilised to put forward recommendations for reducing process-related cost and overhead within organisations.

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“…Evolutionary techniques allow for the production and exploration of a population of diverse process designs based on a specific set of process requirements (Tiwari, Vergidis and Turner 2010). Wang, Salhi and Fraga (2004) note that process optimisation is a difficult task due to the inherent discontinuous nature of the underlying mathematical models.…”

Section: Introductionmentioning

confidence: 99%

An automated optimisation framework for the development of re-configurable business processes: a web services approach

Vergidis¹,

Turner²,

Alechnovic³

et al. 2013

International Journal of Computer Integrated Manufacturing

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Abstract:The practice of optimising business processes has, until recently, been undertaken mainly as a manual task. This paper provides insights into an automated business process optimisation framework by using web services for the development of re-configurable business processes. The research presented here extends the framework of Vergidis (2008) by introducing web services as a mechanism for facilitating business process interactions, identifying enhancements to support business processes and undertaking three case studies to evaluate the proposed enhancements. The featured case studies demonstrate that an increase in the amount of available web services gives rise to improvements in the business processes generated. This research highlights an increase in the efficiency of the algorithm and the quality of the business process designs that result from the enhancements. Future research directions are proposed for the further improvement of the framework.

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Process design optimisation using embedded hybrid visualisation and data analysis techniques within a genetic algorithm optimisation framework

Cited by 43 publications

References 11 publications

Direct search of feasible region and application to a crashworthy helicopter seat

Direct search of feasible region and application to a crashworthy helicopter seat

Revising history for cost-informed process improvement

An automated optimisation framework for the development of re-configurable business processes: a web services approach

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