Promoting effective goods distribution through route optimization and coordination to attenuate environmental impact

Goods transport has steadily intensified in the last decades and its impact on environment increases analogously. Particularly, goods distribution in towns contributed not only to the negative environmental impact, but also creates congestion. The tendency of frequent deliveries in small parties of goods is growing in the contemporary distribution system following the principle of just in time, JIT. And thus vehicles are partially loaded and the number of vehicles per kilometre increases. The current paper presents the study made on the food distribution in and around Uppsala town to map out the system and to investigate the possibilities of co-ordinated distribution to promote an economically effective and environmentally sustainable distribution system. The project was conducted collaboratively by Swedish University of Agricultural Sciences, SLU, Transport Research Institute, TFK, and the environmental section of Uppsala communal administration. Thirteen producing and distributing companies have participated in the project. The methods employed include conducting series of seminars, field measurement on distribution performance, conduct overall distribution simulation and optimisation, route optimisation in terms of sequences of delivery and distance, and computation of emissions. It was a participatory form of project were the main actors, i.e., producers and distributors actively participated particularly in the seminars where co-distribution constraints, field measurement results and possible solutions were discussed. The measured parameters were time (driving, loading, unloading, motor-idling, resting, exact time of delivery for each customer, start and end of distribution), load carrying capacity utilisation level of vehicles in terms of weight and volume, transport distance, routes of distributions, vehicle’s speed, and geographical locations of producers and delivery points. The latest three parameters were measured using the Global Positioning System, GPS. The measured data was thereafter used to optimise distribution and to compute emissions generated from the vehicles using the distribution planning software, DPS, and the dynamic simulation model, MODTRANS, respectively. All together, 38 routes and 513 deliveries were made with 19 vehicles and the total transport distance was 4322 km. Route optimisation experiments were made for every route. The maximum time saved after optimisation for some companies was about 40% and the maximum distance reduced was about 34%. However, about 16% of the routes were well planned by the drivers. Simulation experiments were also made to observe various possible combinations. It was found that almost all the producers lie very near to each other, and many of them (especially those distributing in the suburbs of Uppsala) follow similar routes and acquire many common customers. Combination of two or more routes reduced haulage by about 45%. Those companies distributing bread products meet very often at the delivery points, and follow one another to the next delivery points. Total optimisations of distribution was made for the whole routes and by group, for instance, bread or meat distributions. Total optimisation reduced the number of vehicles by 42%, routes by 58% and distance by 39%. The vehicles’ load carrying capacity utilisation at the initial point of loading varied between 5% to 90%. Motor-idling at the delivery points was observed. Out of the 38 routes, the drivers allow the motor idling during unloading for 25 routes. The time distribution for driving, stop, and stop with motor idling were 71%, 21%, and 8% respectively. The environmental impact of the contemporary distribution routine was estimated by computing emissions emanated from the vehicles for each route and presented in the report. Parameters such as vehicle’s weight, load, road conditions (slopes of the roads), vehicle’s speed and motor idling, were considered for emission estimation. It may be concluded that, there is a potential to implement co-ordination in two stages. Companies distributing similar food products in the same route could develop a common delivery route without any technical development of vehicles. Those distributing in the same route, but their commodities require different temperature in the vehicle, may require vehicles with different compartments with different temperature.