Business rules are widely used within the services
sector. They provide consistency and allow relatively unskilled staff
to process complex transactions correctly. But there are many
examples where the rules themselves have an impact on the costs and
profits of an organisation. Financial services, transport and human
services are areas where the rules themselves can impact the bottom
line in a predictable way. If this is the case, how can we find that set
of rules that maximise profit, performance or customer service, or
any other key performance indicators? The manufacturing, energy
and process industries have embraced mathematical optimisation
techniques to improve efficiency, increase production and so on. This
paper explores several real world (but simplified) problems in the
services sector and shows how business rules can be optimised. It
also examines the similarities and differences between the service
and other sectors, and how optimisation techniques could be used to
deliver similar benefits.
[1] Andreescu, A, Methodological approaches based on business rules,
Informatica Economica Journal, Vol XII, Issue 3, pp 23-27, 2008
[2] Taylor, J, Decision Management Systems: A Practical Guide to Using
Business Rules and Predictive Analytics, IBM Press, September 30,
2011, ISBN 0-13-288438-0
[3] Harmon, P, Business Process Management Today and Tomorrow, M.
Dumas, M. Reichert, and M.-C. Shan (Eds.): BPM 2008, LNCS 5240, p.
1, 2008, Springer-Verlag
[4] Vergidis, K, Business Process Optimisation Using and Evolutionary
Multi-Objective Framework, PhD Thesis, 2008
[5] Dormer, A, Hybrid Optimisation System for Solving Planning and
Scheduling Problems, COR/INFORMS, Banff, 2004
[6] Ernst, A, et al, Staff scheduling and rostering: A review of applications,
methods and models, European Journal of Operational Research 153
(2004) 3-27, 2004
[7] Zachary, H et al, Supply-Chain Optimisation- players, tools and issues,
OR Insight (2001) 14, 20-30
[8] D'Ariano, A., Conflict Resolution and Train Speed Coordination for
Solving Real-Time Timetable Perturbations, in IEEE Transactions on
Intelligent Transportation Systems, Vol 8. Issue 2, 208-222, 2007
[9] Federal Deposit Insurance Corporation (FDCI), Risk Management
Examination Manual for Credit Card Activities, Chapter VII, FDICDivision
of Supervision and Consumer Protection, March 2007
[10] Dormer, A, Innovations in Recovery Optimisation, AGIFORS, Sao
Paulo, 2005
[11] Lawler, E, et al, Sequencing and scheduling: Algorithms and
complexity, in Handbooks in Operations Research and Management
Science, Volume 4: Logistics of Production and Inventory. Elsevier,
445-522, 1993
[12] Guéret, C, Prins, C, and Sevaux, M, Applications of optimization with
Xpress-MP Revised translation from the French language edition of:
Programmation linéaire by, Editions Eyrolles, Paris, France. Translated
and revised by Susanne Heipcke, Dash Optimization Ltd, 2000
[13] Nocedal and Wright (2006). Numerical Optimization. Springer. ISBN 0-
387-30303-0 Journal of Global Optimization
[14] Ali, M, Törn, A and Viitanen, S, A Numerical Comparison of Some
Modified Controlled Random Search Algorithms, Journal of Global
Optimization,Volume 11, Number 4 (1997) S. P. Bingulac, "On the
compatibility of adaptive controllers (Published Conference Proceedings
style)," in Proc. 4th Annu. Allerton Conf. Circuits and Systems Theory,
New York, 1994, pp. 8-16.
[1] Andreescu, A, Methodological approaches based on business rules,
Informatica Economica Journal, Vol XII, Issue 3, pp 23-27, 2008
[2] Taylor, J, Decision Management Systems: A Practical Guide to Using
Business Rules and Predictive Analytics, IBM Press, September 30,
2011, ISBN 0-13-288438-0
[3] Harmon, P, Business Process Management Today and Tomorrow, M.
Dumas, M. Reichert, and M.-C. Shan (Eds.): BPM 2008, LNCS 5240, p.
1, 2008, Springer-Verlag
[4] Vergidis, K, Business Process Optimisation Using and Evolutionary
Multi-Objective Framework, PhD Thesis, 2008
[5] Dormer, A, Hybrid Optimisation System for Solving Planning and
Scheduling Problems, COR/INFORMS, Banff, 2004
[6] Ernst, A, et al, Staff scheduling and rostering: A review of applications,
methods and models, European Journal of Operational Research 153
(2004) 3-27, 2004
[7] Zachary, H et al, Supply-Chain Optimisation- players, tools and issues,
OR Insight (2001) 14, 20-30
[8] D'Ariano, A., Conflict Resolution and Train Speed Coordination for
Solving Real-Time Timetable Perturbations, in IEEE Transactions on
Intelligent Transportation Systems, Vol 8. Issue 2, 208-222, 2007
[9] Federal Deposit Insurance Corporation (FDCI), Risk Management
Examination Manual for Credit Card Activities, Chapter VII, FDICDivision
of Supervision and Consumer Protection, March 2007
[10] Dormer, A, Innovations in Recovery Optimisation, AGIFORS, Sao
Paulo, 2005
[11] Lawler, E, et al, Sequencing and scheduling: Algorithms and
complexity, in Handbooks in Operations Research and Management
Science, Volume 4: Logistics of Production and Inventory. Elsevier,
445-522, 1993
[12] Guéret, C, Prins, C, and Sevaux, M, Applications of optimization with
Xpress-MP Revised translation from the French language edition of:
Programmation linéaire by, Editions Eyrolles, Paris, France. Translated
and revised by Susanne Heipcke, Dash Optimization Ltd, 2000
[13] Nocedal and Wright (2006). Numerical Optimization. Springer. ISBN 0-
387-30303-0 Journal of Global Optimization
[14] Ali, M, Törn, A and Viitanen, S, A Numerical Comparison of Some
Modified Controlled Random Search Algorithms, Journal of Global
Optimization,Volume 11, Number 4 (1997) S. P. Bingulac, "On the
compatibility of adaptive controllers (Published Conference Proceedings
style)," in Proc. 4th Annu. Allerton Conf. Circuits and Systems Theory,
New York, 1994, pp. 8-16.
@article{"International Journal of Business, Human and Social Sciences:51567", author = "Alan Dormer", title = "Optimising Business Rules in the Services Sector", abstract = "Business rules are widely used within the services
sector. They provide consistency and allow relatively unskilled staff
to process complex transactions correctly. But there are many
examples where the rules themselves have an impact on the costs and
profits of an organisation. Financial services, transport and human
services are areas where the rules themselves can impact the bottom
line in a predictable way. If this is the case, how can we find that set
of rules that maximise profit, performance or customer service, or
any other key performance indicators? The manufacturing, energy
and process industries have embraced mathematical optimisation
techniques to improve efficiency, increase production and so on. This
paper explores several real world (but simplified) problems in the
services sector and shows how business rules can be optimised. It
also examines the similarities and differences between the service
and other sectors, and how optimisation techniques could be used to
deliver similar benefits.", keywords = "Business rules, services, optimisation.", volume = "6", number = "10", pages = "2525-5", }