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%
Routes not designed according to daily demand (i.e. it does not consider demand variability) Long journey time of 11.5 hrs Unnecessary movements and waiting Preparing orders/routes Serving clients Returning empty bottles Closing routes Procedures for serving customers, preparing and closing routes have added activities Serving time in excess of 65% Waiting time to close routes 2. Improvement strategies proposed to reduce STEWs Wastes Waste Description Initiatives Considered Incorrect processing and resource utilisation sequencing defined by drivers. This resulted in the sub-optimal sequencing of customers visits Routes not designed according to demand (i.e. it does not consider demand variability) Semi-dynamic route design Unnecessary movements and waiting Procedures for serving customers, preparing and closing routes have activities. Automating product loading and inspection Assigning inspection, loading and unloading product to warehousing operators Redesigning procedures to serve customers with the use of technology Negotiating full time window flexibility with leaders Table 3. Summary of initiatives suggested and their impact on routing performance indicators Waste Description Initiatives Considered Impact on Incorrect processing and resource utilisation Route sequencing defined by drivers Routes not designed according to daily demand Semi-dynamic design Truck capacity of 35% Distance in excess per of 19% Long journey time of 11.5 hrs Procedures for serving customers, preparing and Automating product loading and inspection Serving time in excess of 65%