Abstract
We develop a multi-objective stochastic programming model for supply chain design under uncertainty using a metaheuristic approach. This is a comprehensive model, which includes both the strategic and tactical levels. The uncertainty regarding demands, supplies, processing and transportation costs is captured by generating discrete scenarios with given probabilities of occurrence. To solve the problem, we use multi-objective simulated annealing and compare the results against the goal attainment technique. Numerical results show that the proposed metaheuristic approach is a very practical solution technique.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Martel, A.: The Design of Production-Distribution Networks: A Mathematical Programming Approach. In: Geunes, J., Pardalos, P.M. (eds.) Supply Chain Optimization, pp. 265–306. Springer (2005)
Geoffrion, A.M., Graves, G.W.: Multicommodity Distribution System Design by Benders Decomposition. Management Science 20, 822–844 (1994)
Martel A., Venkatadri, U.: Optimizing Supply Network Structures under Economies of Scale. In: Proceedings of International Conference on Industrial Engineering and Production Management, Glasgow, United Kingdom (1999)
Vidal, C., Goetschalckx, M.: Strategic Production-Distribution Models: A Critical Review with Emphasis on Global Supply Chain Models. European Journal of Operational Research 98, 1–18 (1997)
Arntzen, B.C., Brown, G.G., Harrison, T.P., Trafton, L.L.: Global Supply Chain Management at Digital Equipment Corporation. Interfaces 25, 69–93 (1995)
Shapiro, J., Singhal, V., Wagner, S.: Optimizing the Value Chain. Interfaces 23, 102–117 (1993)
Azaron, A., Brown, K.N., Tarim, S.A., Modarres, M.: A Multi-Objective Stochastic Programming Approach for Supply Chain Design Considering Risk. International Journal of Production Economics 116, 129–138 (2008)
MirHassani, S.A., Lucas, C., Mitra, G., Messina, E., Poojari, C.A.: Computational Solution of Capacity Planning Models Under Uncertainty. Parallel Computing 26, 511–538 (2000)
Tsiakis, P., Shah, N., Pantelides, C.C.: Design of Multiechelon Supply Chain Networks under Demand Uncertainty. Industrial and Engineering Chemistry Research 40, 3585–3604 (2001)
Santoso, T., Ahmed, S., Goetschalckx, M., Shapiro, A.: A Stochastic Programming Approach for Supply Chain Network Design under Uncertainty. European Journal of Operational Research 167, 96–115 (2005)
Alonso-Ayoso, A., Escudero, L.F., Garin, A., Ortuno, M.T., Perez, G.: An Approach for Strategic Supply Chain Planning under Uncertainty Based on Stochastic 0-1 Programming. Journal of Global Optimization 26, 97–124 (2003)
Suppaptinarm, A., Seffen, K.A., Parks, G.T., Clarkson, P.J.: A Simulated Annealing Algorithm for Multiobjective Optimization. Engineering Optimization 33, 59–85 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Venkatadri, U., Bose, S., Azaron, A. (2012). A Metaheuristic Approach for Supply Chain Network Design Problems. In: Engemann, K.J., Gil-Lafuente, A.M., Merigó, J.M. (eds) Modeling and Simulation in Engineering, Economics and Management. MS 2012. Lecture Notes in Business Information Processing, vol 115. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30433-0_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-30433-0_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30432-3
Online ISBN: 978-3-642-30433-0
eBook Packages: Computer ScienceComputer Science (R0)