Abstract
In this paper, two objective functions related to supply chain performance are considered for optimization during several demand periods. Due to fast and dynamic demand variations in recent times, the supply chains for outsourced components also need agility and quick reconfiguration to adapt to these challenges. For a known demand scenario, the manufacturer must select the optimum combination of suppliers to minimize the total cost of supplies as well as the transportation cost. The two objective functions developed in this model represent the minimization of the total cost of supplies including transportation and maximization of reliability of the set of suppliers. As the two objectives may have trade-offs in many instances, a set of Pareto optimal non-dominated solutions is searched using an evolutionary algorithm called self-organizing migration algorithm or SOMA. A case study on the supply chain of a laptop computer manufacturer is selected from the literature to illustrate the implementation of algorithm to real industrial problems.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
M. Holweg, The three dimensions of responsiveness. Int. J. Oper. Prod. Manage. 25(7), 603–622 (2005)
A. Reichhart, M. Holweg, Creating the customer‐responsive supply chain: A reconciliation of concepts, Int. J Oper Prod Manage. 27(11), 1144–1172, (2007) http://doi.org/10.1108/01443570710830575
B.M. Beamon, Supply chain design and analysis: models and methods. Int. J. Prod. Econ. 55, 281–294 (1998)
M. Dileep, S. Dileep, Managing supply chain flexibility using an integrated approach of classifying, structuring and impact assessment. Int. J. Serv. Oper. Manage. 8(1), 46–50 (2011)
M. Stevenson, M. Spring, Flexibility from a supply chain perspective: definition and review. Int. J. Oper. Prod. Manage. 27(7), 685–713 (2007)
J.B. Naylor, M.N. Mohamed, D. Berry, Leagility: Integrating the lean and agile manufacturing paradigms in the total supply chain, Int J Prod Eco. 62, 107–118 (1999)
A. Gunasekaran, Agile manufacturing: a framework for research and development. Int. J. Prod. Econ. 62, 87–105 (1999)
V.C. Pandey, S. Garg, Analysis of interaction among the enablers of agility in supply chain. J. Adv.Manage. Res. 6(1), 99–114 (2009)
C. Lu, S. Zhang, Reconfiguration based agile supply chain system, in IEEE International Conference on Systems, Man and Cybernetics, Tucson, USA (2001), pp. 1007–1012
M. Christopher, D. Towill, An integrated model for the design of agile supply chains. Int. J. Phys. Distrib. Logistics Manage. 31(4), 235–246 (2001)
Z. Ebrahim, A. Nurul, M. Ahmad, M. Razali, Understanding responsiveness in manufacturing operations, in International Symposium on Research in Innovation and Sustainability, Malacca, Malaysia, 15–16 Oct 2014
M. Catalan, H. Kotzab, Assessing the responsiveness in the Danish mobile phone supply chain. Int. J. Phys. Distrib. Logistics Manage. 33(8), 668–685 (2003)
A.C.C. Carlos, An updated survey of GA-based multi objective optimization techniques. ACM Comput. Surv. 32(2), 109–110 (2000)
K. Hitoshi, T. Tomiyama, M. Nagel, S. Silvester, H. Brezet, A multi-objective reconfiguration method of supply chains through discrete event simulation, in 4th International Symposium on Environmentally Conscious Design and Inverse Manufacturing, Tokyo (2005). pp. 320–325
H. Ding, B. Lyès, X. Xie, A simulation-based multi-objective genetic algorithm approach for networked enterprises optimization. Eng. Appl. Artif. Intell. 19, 609–623 (2006)
S.C. dos Leandro, Self-organizing migration algorithm applied to machining allocation of clutch assembly. Math. Comput. Simul. 80, 427–435 (2009)
S. Roman, Z. Ivan, D. Donald, O. Zuzana, Utilization of SOMA and differential evolution for robust stabilization of chaotic Logistic equation. Comput. Math Appl. 60, 1026–1037 (2010)
I. Zelinka, J. Lampinen, SOMA-self-organizing migrating algorithm, in Proceedings of the 6th International Conference on Soft Computing, Brno, Czech Republic (2000), pp 177–187
P. Kadlec, Z. Raida, A novel multi-objective self-organizing migrating algorithm. Radio Eng. 20(4), 804–809 (2011)
G.C. Onwubolu, B.V. Babu, New Optimization Techniques in Engineering (Springer, Berlin, 2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Pattanaik, L.N., Agarwal, P., Ranjan, S., Narayan, U. (2020). Bi-objective Optimization of a Reconfigurable Supply Chain Using a Self-organizing Migration Algorithm. In: Sahana, S., Bhattacharjee, V. (eds) Advances in Computational Intelligence. Advances in Intelligent Systems and Computing, vol 988. Springer, Singapore. https://doi.org/10.1007/978-981-13-8222-2_4
Download citation
DOI: https://doi.org/10.1007/978-981-13-8222-2_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-8221-5
Online ISBN: 978-981-13-8222-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)