Automating Forward and Reverse Supply Chains in the Context of Industry 4.0

Aitken, J., Harrison, A. (2013). Supply governance structures for reverse logistics systems. International Journal of Operations & Production Management, 33(6), 745-764.10.1108/IJOPM-10-2011-0362Search in Google Scholar

Bishop, C. (2006). Pattern recognition and machine learning. New York: Springer.Search in Google Scholar

Brettel, M., Friederichsen, N., Keller, M., Rosenberg, M., 2014. How Virtualization, Decentralization and Network Building Change the Man-Ufacturing Landscape: An Industry 4.0 Perspective. International Journal of Mechanical, Industrial Science and Engineering, Volume 8, 37-44.Search in Google Scholar

Cerquides, J., Endriss, U., Giovannucci,. A., Rodriguez-Aguilar, J. A. (2007). Bidding languages and winner determination for mixed multi-unit combinatorial auctions. s.l., IJCAI, Morgan Kaufmann Publishers Inc..Search in Google Scholar

Chan, F., Chan, H., Jain, V. (2012). A framework of reverse logistics for the automobile industry. International Journal of Production Research, 50(5), 1318-1331.10.1080/00207543.2011.571929Search in Google Scholar

Collins, J., Ketter, W., Gini, M., Mobasher, B. (2002). A multi-agent negotiation testbed for contracting tasks with temporal and precedence constraints. International Journal of Electronic Commerce, Vol. 7.10.1080/10864415.2002.11044260Search in Google Scholar

Cooper, M., Lambert, D., Pagh, J. D. (1997). Supply chain management: more than a new name for logistics. The International Journal of Logistics Management, 8(1), 1-9.10.1108/09574099710805556Search in Google Scholar

Demirel, E., Demirel, N., Gökçen, H. (2014). A mixed integer linear programming model to optimize reverse logistics activities of end-of-life vehicles in Turkey. Journal of Cleaner Production.Search in Google Scholar

Fleischmann, M. (2001). Quantitative Models for Reverse Logistics. In: Lecture Notes in Economics and Mathematical Systems., p. 501.10.1007/978-3-642-56691-2Search in Google Scholar

Geissbauer, R., Vedsø, J., Schrauf, S. (2016). A Strategist’s Guide to Industry 4.0: Global businesses are about to integrate their operations into a seamless digital whole, and thereby change the world.. Strategy and Business.Search in Google Scholar

Giovannucci, A., Cerquides, J., Rodríguez-Aguilar, J. (2010). Composing supply chains through multiunit combinatorial reverse auctions with transformability relationships among goods. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 40(4), 767-778.10.1109/TSMCA.2009.2037236Search in Google Scholar

Giovannucci, A., Vinyals, M., Rodriguez-Aguilar, J., Cerquides, J. (2008). Computationally-efficient winner determination for mixed multi-unit combinatorial auctions. s.l., Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems, Vol. 2, 1071–1078.10.1145/1329125.1329253Search in Google Scholar

Govindan, K., Soleimani, H., Kannan, D. (2015). Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future, European Journal of Operational Research, Volume 240, Issue 3, 603-62610.1016/j.ejor.2014.07.012Search in Google Scholar

Grabara, J., Man, M., Kolcun, M. (2014). The benefits of reverse logistics. International Letters of Social and Humanistic Sciences, Vol. 15, 138-147.10.18052/www.scipress.com/ILSHS.26.138Search in Google Scholar

Guide, V., Van Wassenhove, L. (2009). The evolution of closed-loop supply chain research. Operations Research, 57(1), 10-18.10.1287/opre.1080.0628Search in Google Scholar

Hahn, T. (2014). Future of Manufacturing - View on enabling technologies, s.l.: Siemens Corporate Technology.Search in Google Scholar

Khan, S. A. R., Qianli, D., SongBo, W., Zaman, K., 2017. Environmental logistics performance indicators affecting per capita income and sectoral growth: evidence from a panel of selected global ranked logistics countries. Environmental Science and Pollution Research, 24(2), 1518-1531.10.1007/s11356-016-7916-2Search in Google Scholar

Khan, S. A. R., Zaman, K., Zhang, Y. (2016). The relationship between energy-resource depletion, climate change, health resources and the environmental Kuznets curve: Evidence from the panel of selected developed countries. Renewable and Sustainable Energy Review, Vol. 62, 468–477.10.1016/j.rser.2016.04.061Search in Google Scholar

Kong, Y., Zhang M., Ye, D. (2017) A Belief Propagation-based Method for Task Allocation in Open and Dynamic Cloud Environments, Knowledge-Based Systems, vol. 115, 123-132.10.1016/j.knosys.2016.10.016Search in Google Scholar

Melo, M., Nickel, S., Saldanha-da-Gama, F. (2009). Facility location and supply chain management – A review. European Journal of Operational Research, 196(2), 401-412.10.1016/j.ejor.2008.05.007Search in Google Scholar

Mikhaylov, B., Cerquides, J., Rodriguez-Aguilar, J. (2011). Solving sequential mixed auctions with integer programming. Advances in Artificial Intelligence, Springer, 42-53.10.1007/978-3-642-25274-7_5Search in Google Scholar

Mooij, J. M. (2010). libDAI: A free and open source c++ library for discrete approximate inference in graphical models. Journal of Machine Learning Research, Volume 11, 2169–2173.Search in Google Scholar

Parker, J., Farinelli A., Gini, M. (2017). Max-Sum for Allocation of Changing Cost Tasks, Intelligent Autonomous System. Advances in Intelligent Systems and Computing, vol. 531, 629-642.10.1007/978-3-319-48036-7_46Search in Google Scholar

Patroklos, P., Besoiu, M., 2010. Environmental and economical sustainability of WEEE closed-loop supply chains with recycling: a system dynamics analysis. The International Journal of Advanced Manufacturing Technology, 47(5-8), 475–493.10.1007/s00170-009-2362-7Search in Google Scholar

Penya-Alba, T., Vinyals, M., Cerquides, J., Rodriguez-Aquilar, J. (2012). A scalable Message-Passing Algorithm for Supply Chain Formation. s.l., 26th Conference on Artificial Intelligence.10.1609/aaai.v26i1.8247Search in Google Scholar

Quariguasi Frota Neto, J., Walther, G., Bloemhof, J., van Nunen, J.A.E.E., Spengler, T. (2010). From closed-loop to sustainable supply chains:The WEEE case. International Journal of Production Research, 48(15), 4463-4481.10.1080/00207540902906151Search in Google Scholar

Ravi, V., Shankar, R. (2012). Evaluating alternatives in reverse logistics for automobile organisations. International, 12(1), 32-51.10.1504/IJLSM.2012.047057Search in Google Scholar

Rubio, S., Parra, B. (2014). Reverse Logistics: Overview and Challenges for Supply Chain Management. International Journal of Engineering Business Management, vol. 6.10.5772/58826Search in Google Scholar

Snyder, L. V. (2006). Facility location under uncertainty: A review. IIE Transactions, 38(7), 537-554.10.1080/07408170500216480Search in Google Scholar

Tibben-Lembke, R., Rogers, D. (2002). Differences between forward and reverse logistics in a retail environment. Supply Chain Management: An International Journal, 7(5), 271-282.10.1108/13598540210447719Search in Google Scholar

Walsh, W. E., Wellman, M. P., Ygge, F. (2000). Combinatorial auctions for supply chain formation, Proceedings of the 2nd ACM conference on Electronic commerce.10.1145/352871.352900Search in Google Scholar

Walsh, W., Wellman, M. P. (2003). Decentralized supply chain formation: A market protocol and competitive equilibrium analysis. Journal of Artificail Intelligence Research, Volume 19, 513-567.10.1613/jair.1213Search in Google Scholar

Winsper, M., Chli, M. (2013). Decentralized supply chain formation using max-sum loopy belief propagation. Computational Intelligence, 29(2), 281-309.10.1111/j.1467-8640.2012.00446.xSearch in Google Scholar

Winsper, M., Chli, M. (2010). Decentralised supply chain formation: A belief propagation-based approach. Agent-Mediated Electronic Commerce.Search in Google Scholar

Winsper, M., Chli, M. (2012). Using the max-sum algorithm for supply chain formation in dynamic multi-unit environments. s.l.: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems.Search in Google Scholar