This work proposes an innovative methodology for the reduction of the operation costs and pollutant
emissions involved in the waste collection and transportation. Its innovative feature lies in combining
vehicle route optimization with that of waste collection scheduling. The latter uses historical data of
the filling rate of each container individually to establish the daily circuits of collection points to be visited,
which is more realistic than the usual assumption of a single average fill-up rate common to all the
system containers. Moreover, this allows for the ahead planning of the collection scheduling, which permits
a better system management. The optimization process of the routes to be travelled makes recourse
to Geographical Information Systems (GISs) and uses interchangeably two optimization criteria: total
spent time and travelled distance. Furthermore, rather than using average values, the relevant parameters
influencing fuel consumption and pollutant emissions, such as vehicle speed in different roads
and loading weight, are taken into consideration. The established methodology is applied to the glasswaste
collection and transportation system of Amarsul S.A., in Barreiro. Moreover, to isolate the influence
of the dynamic load on fuel consumption and pollutant emissions a sensitivity analysis of the vehicle
loading process is performed. For that, two hypothetical scenarios are tested: one with the collected volume
increasing exponentially along the collection path; the other assuming that the collected volume
decreases exponentially along the same path. The results evidence unquestionable beneficial impacts
of the optimization on both the operation costs (labor and vehicles maintenance and fuel consumption)
and pollutant emissions, regardless the optimization criterion used. Nonetheless, such impact is particularly
relevant when optimizing for time yielding substantial improvements to the existing system:
potential reductions of 62% for the total spent time, 43% for the fuel consumption and 40% for the emitted
pollutants. This results in total cost savings of 57%, labor being the greatest contributor, representing over
€11,000 per year for the two vehicles collecting glass-waste. Moreover, it is shown herein that the
dynamic loading process of the collection vehicle impacts on both the fuel consumption and on pollutant
emissions.