HUPMOBILE’s expert partner KTH Royal Institute of Technology in cooperation with the Logistics Association PLAN and  Södertälje Science park  had organized Research & Application Conference – PLAN 2020 on October 21 in online format.  The conference was participated by various stakeholders and speakers and featured 3 parallel sessions – Engineering to Order, Service management and Digitalisation throughout the day. 

Within the digitalisation session of the conference Amita Singh from KTH presented – “Towards Carbon Neutral Logistics: A Simulation-based Optimization Approach”, based on the research activities in the HUPMOBILE project. A summary of her presentation is below.

Faced with demands of sustainability and reducing carbon emissions together with the existing requirements of minimizing waiting times and costs incurred, the field of transport and logistics is witnessing a paradigm shift. Stakeholders pay increased attention to streamlining their operations with respect to the abovementioned criteria. So far, the effect of vehicular flow on the environment was seen as a by-product of overall optimization of costs incurred. However, now, with the companies moving towards sustainability and carbon neutrality, consequently, the effects of vehicular flow on the environment have come to the forefront of problem-solving together with the cost optimization. 

Simulation-based optimization has been widely used in controlling traffic lights using traffic microsimulators and, hence, the controlling of the vehicular flow through a town, but not much effort has been made in the area of minimizing carbon emissions in a traffic flow and the literature on it remains sparse. The presentation integrates operational and environmental boundaries by proposing a specific methodology combining simulation and multi-objective evolutionary algorithm to simultaneously optimize carbon emissions and costs incurred. The experimental set-up is shown below:

kth_simulation_case.png

The simulation is done using Simulation of Urban Mobility (SUMO) software together with the map import of the map from OpenStreetMap and combining it with multi-objective evolutionary algorithm (NSGA II). The case illustrates how (re)routing of production logistics through the town is done to optimize multiple objectives: minimizing carbon emissions and traditional costs metrics. The optimization procedure brings forth a Pareto (80/20 rule) optimal front highlighting the trade-offs involved in the decision. The multiobjective optimization approach   provides all stakeholders, including policymakers, town administration and company personnel responsible for logistics, with a set of alternatives to choose from. It will allow the users to take their decision by evaluating a set of criteria, such as time and emissions or noise and emissions.

Text by Amita Singh 
Cover image & in text illustration by Amita Singh