Adulyasak, Y., Cordeau, J.-F., & Jans, R. (2013). Formulations and branch-and-cut algorithms for multivehicle production and inventory routing problems. INFORMS Journal on Computing, 26(1), 103-120.
Ahmadi Javid, A., & Azad, N. (2010). Incorporating location, routing and inventory decisions in supply chain network design. Transportation Research Part E: Logistics and Transportation Review, 46(5), 582-597.
Bell, W. J., Dalberto, L. M., Fisher, M. L., Greenfield, A. J., Jaikumar, R., Kedia, P., . . . Prutzman, P. J. (1983). Improving the distribution of industrial gases with an on-line computerized routing and scheduling optimizer. Interfaces, 13(6), 4-23.
C Montgomery, D. (1997). Montgomery Design and Analysis of Experiments.
Demir, E. (2012). Models and algorithms for the pollution-routing problem and its variations. University of Southampton.
Golden, B., Assad, A., Levy, L., & Gheysens, F. (1984). The fleet size and mix vehicle routing problem. Computers & Operations Research, 11(1), 49-66.
Halim, H., & Moin, N. (2014). Solving inventory routing problem with backordering using Artificial Bee Colony. Paper presented at the Industrial Engineering and Engineering Management (IEEM), 2014 IEEE International Conference on.
Han, K.-H., & Kim, J.-H. (2002). Quantum-inspired evolutionary algorithm for a class of combinatorial optimization. Evolutionary Computation, IEEE Transactions on, 6(6), 580-593.
Han, K.-H., & Kim, J.-H. (2004). Quantum-inspired evolutionary algorithms with a new termination criterion, H ε gate, and two-phase scheme. Evolutionary Computation, IEEE Transactions on, 8(2), 156-169.
Kaye, P., Laflamme, R., & Mosca, M. (2007). An introduction to quantum computing.
Koç, Ç., Bektaş, T., Jabali, O., & Laporte, G. (2014). The fleet size and mix pollution-routing problem. Transportation Research Part B: Methodological, 70, 239-254.
Kopfer, H., & Kopfer, H. (2013). Emissions Minimization Vehicle Routing Problem in Dependence of Different Vehicle Classes. In H.-J. Kreowski, B. Scholz-Reiter, & K.-D. Thoben (Eds.), Dynamics in Logistics (pp. 49-58): Springer Berlin Heidelberg.
Kwon, Y.-J., Choi, Y.-J., & Lee, D.-H. (2013). Heterogeneous fixed fleet vehicle routing considering carbon emission. Transportation Research Part D: Transport and Environment, 23, 81-89. doi: http://dx.doi.org/1016/10/j.trd.04/2013.001
Lee, H. L., & Seungjin, W. (2008). The whose, where and how of inventory control design. Supply Chain Management Review, 12(8), 22-29.
Lerhlaly, S., Lebbar, M., Allaoui, H., Ouazar, D., & Afifi, S. (2016). An Integrated Inventory Location Routing Problem Considering CO2 Emissions.
Lin, C., Choy, K. L., Ho, G. T., Chung, S., & Lam, H. (2014). Survey of green vehicle routing problem: Past and future trends. Expert Systems with Applications, 41(4), 1118-1138.
Mirzapour Al-e-hashem, S., & Rekik, Y. (2013). Multi-product multi-period Inventory Routing Problem with a transshipment option: A green approach. International Journal of Production Economics.
Niakan, F., & Rahimi, M. (2015). A multi-objective healthcare inventory routing problem; a fuzzy possibilistic approach. Transportation Research Part E: Logistics and Transportation Review, 80, 74-94.
Platel, M. D., Schliebs, S., & Kasabov, N. (2007). A versatile quantum-inspired evolutionary algorithm. Paper presented at the Evolutionary Computation, 2007. CEC 2007. IEEE Congress on.
Sbihi, A., & Eglese, R. (2007). Combinatorial optimization and Green Logistics. 4OR, 5(2), 99-116. doi: 1007/10/s10288-007-0047-3
Shao, S., & Huang, G. Q. (2014). A SHIP Inventory Routing Problem with Heterogeneous Vehicles under Order-Up-To Level Policies. Paper presented at the IIE Annual Conference. Proceedings.
Soysal, M., Bloemhof-Ruwaard, J. M., Haijema, R., & van der Vorst, J. G. (2015). Modeling an Inventory Routing Problem for perishable products with environmental considerations and demand uncertainty. International Journal of Production Economics, 164, 118-133.
Soysal, M., Bloemhof-Ruwaard, J. M., Haijema, R., & van der Vorst, J. G. (2016). Modeling a green inventory routing problem for perishable products with horizontal collaboration. Computers & Operations Research.
Send comment about this article