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Integrated supply chain design models: a survey and future research directions
Taking market forces into account in the design of production-distribution networks: A positioning by anticipation approach
1. | Universiét Laval, FOR@C Research Consortium, Network Organization Technology Research Center (CENTOR), Sainte-Foy, Québec, G1K7P4, Canada |
2. | Université Laval, FOR@C Research Consortium, Network Organization Technology Research Center (CENTOR), Sainte-Foy, Québec, G1K7P4, Canada, Canada |
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Chjan C. Lim, Joseph Nebus, Syed M. Assad. Monte-Carlo and polyhedron-based simulations I: extremal states of the logarithmic N-body problem on a sphere. Discrete & Continuous Dynamical Systems - B, 2003, 3 (3) : 313-342. doi: 10.3934/dcdsb.2003.3.313 |
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Azam Moradi, Jafar Razmi, Reza Babazadeh, Ali Sabbaghnia. An integrated Principal Component Analysis and multi-objective mathematical programming approach to agile supply chain network design under uncertainty. Journal of Industrial & Management Optimization, 2019, 15 (2) : 855-879. doi: 10.3934/jimo.2018074 |
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Michael B. Giles, Kristian Debrabant, Andreas Rössler. Analysis of multilevel Monte Carlo path simulation using the Milstein discretisation. Discrete & Continuous Dynamical Systems - B, 2019, 24 (8) : 3881-3903. doi: 10.3934/dcdsb.2018335 |
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Michelle L.F. Cheong, Rohit Bhatnagar, Stephen C. Graves. Logistics network design with supplier consolidation hubs and multiple shipment options. Journal of Industrial & Management Optimization, 2007, 3 (1) : 51-69. doi: 10.3934/jimo.2007.3.51 |
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Abdelghani Bouras, Lotfi Tadj. Production planning in a three-stock reverse-logistics system with deteriorating items under a continuous review policy. Journal of Industrial & Management Optimization, 2015, 11 (4) : 1041-1058. doi: 10.3934/jimo.2015.11.1041 |
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Olli-Pekka Tossavainen, Daniel B. Work. Markov Chain Monte Carlo based inverse modeling of traffic flows using GPS data. Networks & Heterogeneous Media, 2013, 8 (3) : 803-824. doi: 10.3934/nhm.2013.8.803 |
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