manufacturing firms”, Vol. 129, No. International Journal of Production Economics, 2, pp. 251-261. Yu, B., Ma, N., Cai, W., Li, T., & Yuan, X. (2013), ant colony optimisation for the “Improved dynamic multi-depot vehicle routing problem”, International Journal of Logistics Vol. 16, No. 2, pp. 144-157. Research and Applications, Yu, V.F., Hu, K.J., & Chang, A.Y. (2015), interactive approach for the multi-objective “An transportation problem with interval parameters”, International Journal of Production Vol. 53, No. 4, pp. 1051-1064. Research, Zander, S., Trang, S., & Kolbe, L.M., (2015), of network governance: a “Drivers multitheoretic perspective with insights from case studies in the German wood industry”, DOI:10.1016/j.jclepro.2015.03.010, in Journal of Cleaner Production, press. R., & Yun, W.Y. (2009), reactive tabu search algorithm for the multi-depot “A container truck transportation problem”, Transportation Research Part E: Logistics Vol. 45, No. 6, pp. 904-914. and Transportation Review, Zhang, J., Li, W., & Qiu, F. (2014), single-depot vehicle scheduling problem: “Optimizing fixed-interval model and algorithm”, Journal of Intelligent Transportation Systems: Vol. 19, No. 3, pp. 215-224. Technology, Planning, and Operations, Zhong, H., Hall, R.W., & Dessouky, M. (2007), planning and vehicle dispatching “Territory with driver learning”, Vol. 41, No. 1, pp. 74-89. Transportation Science, Table 1. Summary of relevant STEWs Wastes Operation Activity Description Impact on Route sequencing Truck capacity Incorrect defined by drivers. under-utilisation of processing and Transporting product This resulted in 35% resource to customers sequencing of Distance in excess utilisation the customers visits per route of 19%
manufacturing firms”, International Journal of Production Economics, Vol. 129, No. 2, pp. 251-261. Yu, B., Ma, N., Cai, W., Li, T., & Yuan, X. (2013), “Improved ant colony optimisation for the dynamic multi-depot vehicle routing problem”, International Journal of Logistics Research and Applications, Vol. 16, No. 2, pp. 144-157. Yu, V.F., Hu, K.J., & Chang, A.Y. (2015), “An interactive approach for the multi-objective transportation problem with interval parameters”, International Journal of Production Research, Vol. 53, No. 4, pp. 1051-1064. Zander, S., Trang, S., & Kolbe, L.M., (2015), “Drivers of network governance: a multitheoretic perspective with insights from case studies in the German wood industry”, Journal of Cleaner Production, DOI:10.1016/j.jclepro.2015.03.010, in press. R., & Yun, W.Y. (2009), “A reactive tabu search algorithm for the multi-depot container truck transportation problem”, Transportation Research Part E: Logistics and Transportation Review, Vol. 45, No. 6, pp. 904-914. Zhang, J., Li, W., & Qiu, F. (2014), “Optimizing single-depot vehicle scheduling problem: fixed-interval model and algorithm”, Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Vol. 19, No. 3, pp. 215-224. Zhong, H., Hall, R.W., & Dessouky, M. (2007), “Territory planning and vehicle dispatching with driver learning”, Transportation Science, Vol. 41, No. 1, pp. 74-89. Table 1. Summary of relevant STEWs Wastes Operation Activity Description Impact on Incorrect processing and resource utilisation Transporting product to customers Route sequencing defined by drivers. This resulted in sequencing of the customers visits Truck capacity under-utilisation of 35% Distance in excess per route of 19%
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