Abstract. This paper investigates the influence of gradient and payload correction factors used within a CO2 emission model on the solutions to shortest path and travelling salesman problems when applied to freight delivery.Problem instances based on real life examples using the road network of Scotland are studied. Solutions are obtained using a range of metrics and vehicles. The results are compared to determine if the inclusion of gradient and payload as inputs to the emission model have any influence on the final routes taken by vehicles or the order of visiting customers. For the problem instances studied no significant influence was found. However for vehicle routing problems with large differences in payload and hilly road networks further investigation is needed.

Abstract. This paper examines the issues surrounding the effects of using vehicle emissions as the fitness criteria when solving routing problems using evolutionary techniques. The case-study examined is that of the Travelling Salesman Problem (TSP) based upon the road network within the City of Edinburgh, Scotland. A low cost path finding algorithm (A*) is used to build paths through the street network between delivery points. The EA is used to discover tours that utilise paths with low emissions characteristics. Two methods of estimating CO2 emissions are examined; one that utilises a fuel consumption model and applies it to an estimated drive cycle and one that applies a simplistic CO2 calculation model that focuses on average speeds over street sections. The results of these two metrics are compared with each other and with results obtained using a traditional distance metric.

An evolutionary Multi-Objective Algorithm (MOA) is used to investigate the trade-off between CO2 savings, distance and number of vehicles used in a typical vehicle routing problem with Time Windows (VRPTW). A problem set is derived containing three problems based on accurate geographical data which encapsulates the topology of streets as well as layouts and characteristics of junctions. This is combined with realistic speed-flow data associated with road-classes and a power-based instantaneous fuel consumption model to calculate CO2 emissions, taking account of drive-cycles. Results obtained using a well-known MOA with twin objectives show that it is possible to save up to 10% CO2, depending on the problem instance and ranking criterion used.