Decision-Making for Supply Chain Integration: Supply Chain by Lixing Yeung, CKM Lee (auth.), Hing Kai Chan, Fiona Lettice,

By Lixing Yeung, CKM Lee (auth.), Hing Kai Chan, Fiona Lettice, Olatunde Amoo Durowoju (eds.)

Effective offer chain integration, and the tight co-ordination it creates, is an important pre-requisite for profitable offer chain administration. Decision-Making for provide Chain Integration is a realistic reference on contemporary study within the zone of provide chain integration concentrating on disbursed decision-making difficulties. contemporary purposes of varied decision-making instruments for integrating offer chains are lined together with chapters focusing on:

Supplier choice, pricing procedure and stock judgements in multi-level offer chains,
RFID-enabled allotted decision-making,
Operational chance matters and time-critical decision-making for delicate logistics nodes, Modelling finish to finish approaches to enhance offer chain integration, and
Integrated structures to enhance carrier supply and optimize source use.

Decision-Making for offer Chain Integration presents an perception into the instruments and methodologies of this box with help from real-life case experiences demonstrating winning software of assorted decision-making options. through overlaying this type of variety of issues during this means, Decision-Making for offer Chain Integration is an invaluable reference for researchers trying to improve their wisdom or locate strength new avenues of analysis.

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Crossdocking JIT scheduling with time windows. Journal of Operation Research Society, 55, 1342–1351. G. (2008). Optimal product allocation for crossdocking and warehousing operations in FMCG supply chain. In Proceedings of the IEEE International Conference on Service Operations and Logistics, and Informatics (pp. 2963–2968). , Low, M. Y. , & Lim, R. Y. G. (2009). Optimal decision-making on product allocation for cross-docking and warehousing operations. International Journal of Services Operations and Informatics, 4, 352–365.

9 Product types results L. 523321s Total cost $3,311 $7,510 $17,477 Fig. 8 No. of variables vs. no. of product types to the linear relationship between the number of product types and the number of variables involved. To sum up, the key challenge in this project is to speed up the GA iterations for large problem size. As mentioned throughout this book chapter, GA randomly creates solutions and test for their feasibilities against the 6 constraints set in the model. In fact, the amount of randomness can be greatly reduced by ensuring the creation of solutions that obey the first 3 constraints using filters.

Monitoring Actors (MA) modelling the intelligent actors of SSC are the main elements of this layer. They establish metrics to evaluate the performance of the group and consequently act on the other two layers. Hence, MA are the components responsible of controlling and decision-making into a SSC and of the coordination of the activities for the overall supply chain. 30 J. Tounsi et al. SSC Monitoring System Decision Measurement Execution System Observation Action Physical System Fig. 5 Layers of the SSC (Tounsi et al.

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