The multi-objective Steiner pollution-routing problem on congested urban road networks

This paper introduces the Steiner Pollution-Routing Problem (SPRP) as a realistic variant of the PRP that can take into account the real operating conditions of urban freight distribution. The SPRP is a multi-objective, time and load dependent, fleet size and mix PRP, with time windows, flexible departure times, and multi-trips on congested urban road networks, that aims at minimising three objective functions pertaining to (i) vehicle hiring cost, (ii) total amount of fuel consumed, and (iii) total makespan (duration) of the routes. The paper focuses on a key complication arising from emissions minimisation in a time and load dependent setting, corresponding to the identification of the full set of the eligible road-paths between consecutive truck visits a priori, and to tackle the issue proposes new combinatorial results leading to the development of an exact Path Elimination Procedure (PEP). A PEP-based Mixed Integer Programming model is further developed for the SPRP and embedded within an efficient mathematical programming technique to generate the full set of the non-dominated points on the Pareto frontier of the SPRP. The proposed model considers truck instantaneous Acceleration/Deceleration (A/D) rates in the fuel consumption estimation, and to address the possible lack of such data at the planning stage, a new model for the construction of reliable synthetic spatiotemporal driving cycles from available macroscopic traffic speed data is introduced. Several analyses are conducted to: (i) demonstrate the added value of the proposed approach, (ii) exhibit the trade-off between the business and environmental objectives on the Pareto front of the SPRP, (iii) show the benefits of using multiple trips, and (iv) verify the reliability of the proposed model for the generation of driving cycles. A real road network based on the Chicago's arterial streets is also used for further experimentation with the proposed PEP algorithm. © 2019 Elsevier Lt

Mathematical models and solution algorithms for the vehicle routing problem with environmental considerations

Urban freight distribution is essential for the functioning of urban economies. However, it is contributing significantly to problems such as traffic congestion and environmental pollution. The main goal of this research is to contribute to greening urban freight distribution by developing new mathematical models and solution algorithms pertaining to the two major steams in Vehicle Routing Problems (VRPs) with environmental considerations: (i) VRPs with an explicit fuel consumption estimation component as a proxy for emissions, and (ii) VRPs with vehicles in the fleet that run on a cleaner alternative fuel such as electricity. In the first stream, this thesis develops and solves a new realistic multi-objective variant of the pollution-routing problem, referred to as the Steiner Pollution-Routing Problem (SPRP), that is studied directly on the original urban roadway network. The proposed variant is capable of incorporating the real operating conditions of urban freight distribution, and striking a balance between traditional business and environmental objectives, while integrating all factors that have a major impact on fuel consumption, including the time-varying congestion speed, vehicle load, vehicle’s physical and mechanical characteristics, and acceleration and deceleration rates. The thesis develops new combinatorial results that facilitate problem solution on the original roadway network and also introduces new mathematical models for synthesizing the expected second-by-second driving cycle of a vehicle over a given road-link at a given time of the day. New efficient multi-objective optimisation heuristics are also developed for addressing realistic instances of the SPRP. On the other hand, in the latter stream discussed above, to tackle the significantly impeding problem of range anxiety in the face of goods distribution using Electric Commercial Vehicles (ECVs), a paradigm shift in the routing of ECVs is proposed by introducing the Electric Vehicle Routing Problem with Synchronised Ambulant Battery Swapping/Recharging (EVRP-SABS). The proposed problem exploits new technological developments corresponding to the possibility of mobile battery swapping (or recharging) of ECVs using a Battery Swapping Van (BSV). In the EVRP-SABS, routing takes place in two levels for the ECVs that carry out delivery tasks, and for the BSVs that provide the running ECVs with fully charged batteries on their route. There is, therefore, a need to establish temporal and spatial synchronisations between the vehicles in the two levels and to do so new combinatorial results and a new solution algorithm is proposed

Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios

The electric vehicle routing problem with time windows and synchronised mobile battery swapping

This paper introduces an alternative to intra-route recharging of Electric Commercial Vehicles (ECVs) used for freight distribution by exploiting new pertinent technological developments that make mobile battery swapping possible. The Electric Vehicle Routing Problem with Time Windows and Synchronised Mobile Battery Swapping (EVRPTW-SMBS) is introduced in which route planning is carried out in two interdependent levels: (i) for the ECVs to deliver customers’ demands, and (ii) for the Battery Swapping Vans (BSVs) to swap the depleted battery on an ECV with a fully charged one at a designated time and space. Each BSV route can provide the battery swapping service to multiple ECVs, and each ECV can extend its autonomy by requesting the battery swapping service for as many times as required with no need to divert from its original delivery route. The EVRPTW-SMBS opens up multiple opportunities to facilitate eco-friendly goods distribution using ECVs and brings in extra flexibility and cost savings. At the same time, it is a challenging problem to tackle mainly due to the interdependence problem that stems from the spatio-temporal synchronisation requirement between the vehicles in the two levels (i.e. ECVs and BSVs). To tackle these complications, the paper proposes a methodology for exact evaluation of an EVRPTW-SMBS solution based on a two-stage hybridisation of a dynamic programming and an integer programming algorithm, and places the resulting procedure at the heart of an intensified large neighbourhood search algorithm to solve instances of the EVRPTW-SMBS efficiently. A library of EVRPTW-SMBS test instances is developed and used to demonstrate the added value of the proposed problem variant and the efficiency of the proposed algorithms. Our results demonstrate the benefits of using BSVs in the design of the delivery routes for ECVs, and indicate that a particular variant of the proposed algorithms which is based on a specific lexicographical decomposition routine can efficiently approximate the optimal solution to the EVRPTW-SMBS

Improved shear strength performance of compacted rubberized clays treated with sodium alginate biopolymer

This study examines the potential use of sodium alginate (SA) biopolymer as an environmentally sustainable agent for the stabilization of rubberized soil blends prepared using a high plasticity clay soil and tire-derived ground rubber (GR). The experimental program consisted of uniaxial compression and scanning electron microscopy (SEM) tests; the former was performed on three soil–GR blends (with GR-to-soil mass ratios of 0%, 5% and 10%) compacted (and cured for 1, 4, 7 and 14 d) employing distilled water and three SA solutions—prepared at SA-to-water (mass-tovolume) dosage ratios of 5, 10 and 15 g/L—as the compaction liquid. For any given GR content, the greater the SA dosage and/or the longer the curing duration, the higher the uniaxial compressive strength (UCS), with only minor added benefits beyond seven days of curing. This behaviour was attributed to the formation and propagation of so-called “cationic bridges” (developed as a result of a “Ca2+/Mg2

The synergistic effect of operational research and big data analytics in greening container terminal operations: A review and future directions

Container Terminals (CTs) are continuously presented with highly interrelated, complex, and uncertain planning tasks. The ever-increasing intensity of operations at CTs in recent years has also resulted in increasing environmental concerns, and they are experiencing an unprecedented pressure to lower their emissions. Operational Research (OR), as a key player in the optimisation of the complex decision problems that arise from the quay and land side operations at CTs, has been therefore presented with new challenges and opportunities to incorporate environmental considerations into decision making and better utilise the ‘big data’ that is continuously generated from the never-stopping operations at CTs. The state-of-the-art literature on OR's incorporation of environmental considerations and its interplay with Big Data Analytics (BDA) is, however, still very much underdeveloped, fragmented, and divergent, and a guiding framework is completely missing. This paper presents a review of the most relevant developments in the field and sheds light on promising research opportunities for the better exploitation of the synergistic effect of the two disciplines in addressing CT operational problems, while incorporating uncertainty and environmental concerns efficiently. The paper finds that while OR has thus far contributed to improving the environmental performance of CTs (rather implicitly), this can be much further stepped up with more explicit incorporation of environmental considerations and better exploitation of BDA predictive modelling capabilities. New interdisciplinary research at the intersection of conventional CT optimisation problems, energy management and sizing, and net-zero technology and energy vectors adoption is also presented as a prominent line of future research

EVRPTW-RS-SMBS

This data set contains all instances and the case study data used in the paper "Coordinated routing of electric commercial vehicles with intra-route recharging and en-route battery swapping", published in European Journal of Operational Research

EVRPTW-SMBS

This data set contains all instances used in the paper "The Electric Vehicle Routing Problem with Time Windows and Synchronised Mobile Battery Swapping", published in Transportation Research Part B: Methodological