Abstract
This chapter gives detailed insights into a project for transitioning a wine manufacturing company from a mostly spreadsheet driven business with isolated silo-operated planning units into one that makes use of integrated and optimised decision making by use of modern heuristics. We present a piece of the puzzle - the modelling of business entities and their silo operations and optimizations, and pave the path for a further holistic integration to obtain company-wide globally optimised decisions. We argue that the use of “Computational Intelligence” methods is essential to cater for dynamic, time-variant and non-linear constraints and solve today’s real-world problems exemplified by the given wine supply chain.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ackoff, R.L.: The future of operational research is past. J. Oper. Res. Soc. 30, 93–104 (1979)
Aikens, C.H.: Facility location models for distribution planning. Europ. J. Oper. Res. 22(3), 263–279 (1985)
Altiparmak, F., Gen, M., Lin, L., Paksoy, T.: A genetic algorithm approach for multi-objective optimization of supply chain networks. Comput. Ind. Eng. 51(1), 196–215 (2006)
Boulton, R.B., Singleton, V.L., Bisson, L.F., Kunkee, R.E.: Principles and Practices of Winemaking. Springer (1998)
Caggiano, K.E., Jackson, P.L., Muckstadt, J.A., Rappold, J.A.: Optimizing Service Parts Inventory in a Multiechelon, Multi-Item Supply Chain with Time-Based Customer Service-Level Agreements. Oper. Res. 55(2), 303–318 (2007)
Caglar, D., Li, C.L., Simchi-Levi, D.: Two-echelon spare parts inventory system subject to a service constraint. IIE Transactions 36(7), 655–666 (2004)
Chandra, P., Fisher, M.L.: Coordination of production and distribution planning. Europ. J. Oper. Res. 72(3), 503–517 (1994)
Cheng, R., Gen, M., Tsujimura, Y.: A tutorial survey of job-shop scheduling problems using genetic algorithms—i: representation. Comput. Ind. Eng. 30(4), 983–997 (1996)
Clark, A.J., Scarf, H.: Optimal policies for a multi-echelon inventory problem. Manage. Sci. 50(12 suppl.), 1782–1790 (2004)
Coit, D.W., Smith, A.E.: Solving the redundancy allocation problem using a combined neural network/genetic algorithm approach. Comput. Oper. Res. 23(6), 515–526 (1996)
Davis, L.: Job shop scheduling with genetic algorithms. In: Proc. 1st Int. Conf. Genetic Algorithms, pp. 136–140 (1985)
Davis, L.: Embracing complexity. Toward a 21st century supply chain solution (2008), Web-resource http://sdcexec.com/online/printer.jsp?id=9012
Hanssmann, F.: Optimal inventory location and control in production and distribution networks. Oper. Res. 7(4), 483–498 (1959)
Holthaus, O.: Scheduling in job shops with machine breakdowns: an experimental study. Comput. Ind. Eng. 36(1), 137–162 (1999)
Jain, A.K., Elmaraghy, H.A.: Production scheduling/rescheduling in flexible manufacturing. Int. J. Prod. Res. 35(1), 281–309 (1997)
Kutanoglu, E., Sabuncuoglu, I.: Routing-based reactive scheduling policies for machine failures in dynamic job shops. Int. J. Prod. Res. 39(14), 3141–3158 (2001)
Lambert, D.M.: Supply chain management: Implementation issues and research opportunities. Int. J. of Logistics Management 9, 1–20 (1998)
Lee, C.Y., Choi, J.Y.: A genetic algorithm for job sequencing problems with distinct due dates and general early-tardy penalty weights. Comput. Oper. Res. 22(8), 857–869 (1995)
Lee, H., Pinto, J.M., Grossmann, I.E., Park, S.: Mixed-integer linear programming model for refinery short-term scheduling of crude oil unloading with inventory management. Ind. Eng. Chem. Res. 35(5), 1630–1641 (1996)
Levine, J., Ducatelle, F.: Ant colony optimization and local search for bin packing and cutting stock problems. J. Oper. Res. Soc. 55(7), 705–716 (2004)
Liang, K.H., Yao, X., Newton, C., Hoffman, D.: A new evolutionary approach to cutting stock problems with and without contiguity. Comput. Oper. Res. 29(12), 1641–1659 (2002)
Martin, C.H., Dent, D.C., Eckhart, J.C.: Integrated production, distribution, and inventory planning at libbey-owens-ford. Interfaces 23(3), 68–78 (1993)
Naso, D., Surico, M., Turchiano, B., Kaymak, U.: Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete. Europ. J. Oper. Res. 177(3), 2069–2099 (2007)
Oliver, R.K., Webber, M.D.: Supply-chain management: Logistics catches up with strategy. In: Logistics. Chapman and Hall (1982) (Reprint from Outlook)
Petrovic, D., Alejandra, D.: A fuzzy logic based production scheduling/rescheduling in the presence of uncertain disruptions. Fuzzy Sets and Systems 157(16), 2273–2285 (2006)
Potter, M.: The design and analysis of a computational model of cooperative coevolution. Ph.D. Thesis, George Mason University (1997)
Pyke, D.F., Cohen, M.A.: Performance characteristics of stochastic integrated production-distribution systems. Europ. J. Oper. Res. 68(1), 23–48 (1993)
Pyke, D.F., Cohen, M.A.: Multiproduct integrated production–distribution systems. Europ. J. Oper. Res. 74(1), 18–49 (1994)
Stadtler, H., Kilger, C.: Supply Chain Management and Advanced Planning. Springer (2008)
Thomas, D.J., Griffin, P.M.: Coordinated supply chain management. Europ. J. Oper. Res. 94(1), 1–15 (1996)
Toth, P., Vigo, D.: The Vehicle routing problem. Society for Industrial and Applied Mathematics (2001)
Van Laarhoven, P.J.M.: Job shop scheduling by simulated annealing. Oper. Res. 40, 113 (1992)
Vergara, F.E., Khouja, M., Michalewicz, Z.: An evolutionary algorithm for optimizing material flow in supply chains. Comput. Ind. Eng. 43(3), 407–421 (2002)
Vidal, C.J., Goetschalckx, M.: Strategic production-distribution models: A critical review with emphasis on global supply chain models. Europ. J. Oper. Res. 98(1), 1–18 (1997)
Wong, H., Kranenburg, B., van Houtum, G., Cattrysse, D.: Efficient heuristics for two-echelon spare parts inventory systems with an aggregate mean waiting time constraint per local warehouse. OR Spectrum 29(4), 699–722 (2007)
Zhou, G., Min, H., Gen, M.: A genetic algorithm approach to the bi-criteria allocation of customers to warehouses. Int. J. Prod. Econ. 86(1), 35–45 (2003)
Zielinski, K., Weitkemper, P., Laur, R., Kammeyer, K.D.: Parameter study for differential evolution using a power allocation problem including interference cancellation. In: Proc. 2006 IEEE Congr. Evol. Comput., pp. 1857–1864 (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ibrahimov, M., Mohais, A., Ozols, M., Schellenberg, S., Michalewicz, Z. (2013). Advanced Planning in Vertically Integrated Wine Supply Chains. In: Yang, S., Yao, X. (eds) Evolutionary Computation for Dynamic Optimization Problems. Studies in Computational Intelligence, vol 490. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38416-5_17
Download citation
DOI: https://doi.org/10.1007/978-3-642-38416-5_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38415-8
Online ISBN: 978-3-642-38416-5
eBook Packages: EngineeringEngineering (R0)