Canada’s Grain Handling and Transportation System: A GIS-based Evaluation of Potential Policy Changes

This research re-examines both transportation allocation and infrastructure capacity problems associated with moving grain from the Western Canada to export position. The analysis is conducted with geographic information system software using grain industry data. In contrast with historical grain industry logistics methods, the analysis and simulation framework allows us to re-examine logistic solutions in this vast supply chain in the interest of improving overall delivery efficiency. In addition, we find that rail network capacity should not constrain any major expansion of grain movement in the system over the foreseeable future

The effect of customer satisfaction on parcel delivery operations using autonomous vehicles: An agent-based simulation study

The quality of Third-Party Logistics (3PL) services represented by delivery time decides the outcome of customer satisfaction. The result of this satisfaction judges the type of Word of Mouth (WoM) that, if positive, plays a vital role in attracting non-customers who are willing in 3PL services to join as customers. In this paper, we investigate the effect of an essential factor represented by Word of Mouth on the number of customers in 3PL companies. Therefore, an agent-based model for parcel delivery is developed to investigate the impact of social factors such as WoM and other operational factors, including vehicle number and speed, on customer number and satisfaction, average service time, and vehicle utilization. As a methodology, state charts of Vehicle, Customer, Hub agents are developed to mimic the messaging protocols between these agents under the WoM concept. A case study based in 3PL in Jordan is used as a test bench of the developed model. A sensitivity analysis study is conducted to test the developed model's performance, including different levels of influential model parameters such as targeting non-customers parameters by Loyal/Unhappy customers. Key results reveal that the best scenario is achieved when the WoM value equals 10, the vehicle number equals 30, and the vehicle speed equals 60 km/h. These model parameters result in higher customer numbers of 873, vehicle utilization equals 63%, and customer satisfaction equals 99%. Video of our proposed model showing it in action can be found at: https://www.youtube.com/watch?v=3rR4l130-QU

CANADA’S GRAIN HANDLING AND TRANSPORTATION SYSTEM: A GIS-BASED EVALUATION OF POLICY CHANGES

Western Canada is in a post Canadian Wheat Board single-desk market, in which grain handlers face policy, allocation, and logistical changes to the transportation of grains. This research looks at the rails transportation problem for allocating wheat from Prairie to port position, offering a new allocation system that fits the evolving environment of Western Canada’s grain market. Optimization and analysis of the transport of wheat by railroads is performed using geographic information system software as well as spatial and historical data. The studied transportation problem searches to minimize the costs of time rather than look purely at locational costs or closest proximity to port. Through optimization three major bottlenecks are found to constrain the transportation problem; 1) an allocation preference towards Thunder Bay and Vancouver ports, 2) small capacity train inefficiency, and 3) a mismatched distribution of supply and demand between the Class 1 railway firms. Through analysis of counterfactual policies and a scaled sensitivity analysis of the transportation problem, the grains transport system of railroads is found to be dynamic and time efficient; specifically when utilizing larger train capacities, offering open access to rail, and under times of increased availability of supplies. Even under the current circumstances of reduced grain movement and inefficiencies, there are policies and logistics that can be implemented to offer grain handlers in Western Canada with the transportation needed to fulfill their export demands

Operations planning for agricultural harvesters using ant colony optimization

An approach based on ant colony optimization for the generation for optimal field coverage plans for the harvesting operations using the optimal track sequence principle B-patterns was presented. The case where the harvester unloads to a stationary facility located out of the field area, or in the field boundary, was examined. In this operation type there are capacity constraints to the load that a primary unit, or a harvester in this specific case, can carry and consequently, it is not able to complete the task of harvesting a field area and therefore it has to leave the field area, to unload, and return to continue the task one or more times. Results from comparing the optimal plans with conventional plans generated by operators show reductions in the in-field nonworking distance in the range of 19.3-42.1% while the savings in the total non-working distance were in the range of 18-43.8%. These savings provide a high potential for the implementation of the ant colony optimization approach for the case of harvesting operations that are not supported by transport carts for the out-of-the-field removal of the crops, a practice case that is normally followed in developing countries, due to lack of resources

Integrating Public and Private Data Sources for Freight Transportation Planning

The Moving Ahead for Progress in the 21st Century Act (MAP-21) stipulates that state transportation agencies expand their interest in freight initiatives and modeling to support planning efforts, particularly the evaluation of current and future freight transportation capacity necessary to ensure freight mobility. However, the understanding of freight demand and the evaluation of current and future freight transportation capacity are not only determined by robust models, but are critically contingent on the availability of accurate data. Effective partnerships are clearly needed between the public and private sectors to ensure adequate freight planning and funding of transportation infrastructure at the state and local levels. However, establishing partnerships with firms who are both busy and suspicious of data-sharing, remains a challenge. This study was commissioned by the Texas Department of Transportation (TxDOT) to explore the feasibility of TxDOT entering into a data-sharing partnership with representatives of the private sector to obtain sample data for use in formulating a strategy for integrating public and private sector data sources. This report summarizes the findings, lessons learned, and recommendations formed from the outreach effort, and provides a prototype freight data architecture that will facilitate the storage, exchange, and integration of freight data through a data-sharing partnership.Texas Department of Transportation Research and Technology Implementation Office P.O. Box 5080 Austin, TX 78763-5080Civil, Architectural, and Environmental Engineerin

Biomass supply chain event management

 D. K. Folinas1, D. D. Bochtis2, C. G. Sørensen2, P. Busato3(1. ATEI Thessaloniki, Department of Logistics, Greece; 2. Department of Biosystems Engineering, Faculty of Agricultural Sciences, Aarhus University, Blichers Alle´ 20, P.O. box 50;   3. DEIAFA Department,Faculty of Agriculture, University of Turin, Via Leonardo da Vinci 44, 10095, Grugliasco, Turin, Italy) Abstract: The biomass supply chain constitutes a system that is highly dynamic and stochastic.  The developed and proposed systems architectures for the management of the supply chains of typical industrial products do not directly apply to the case of the biomass supply chain

AN AGENT-BASED SIMULATION MODEL TO INVESTIGATE THE PRICING OF RURAL ROADS IN SASKATCHEWAN

Industry in Saskatchewan, including natural resource, manufacturing and agriculture, is dependent on road infrastructure to reach suppliers and markets. The 296 Rural Municipalities (RMs) in Saskatchewan are responsible for the construction and provision of the extensive rural road network consisting of mostly gravel roads, which can be costly to maintain under heavy vehicle traffic. In general, road users do not directly pay the road provider for their road use; however, the decisions of road users can affect the costs incurred by road providers and vice versa. The goal of this research was to determine the feasibility of applying an agent-based model (ABM) to represent and compare the road use and road provision of a rural road network in Saskatchewan. The main objective was to develop an ABM to determine whether pricing a rural road network on an incremental cost basis would result in a net benefit when considering combined road use and road provision costs. The developed ABM included: road segments, nodes (intersections), road users, and a road provider. Simple heuristics were used to represent road use and road provision decision making, including least cost routing and traffic-based prioritization for road upgrade decisions. Vehicle traffic in the model was generated based on exogenous origin-destination (OD) inputs. The ABM was developed using a hypothetical road network and was applied to a case study rural road network. The permit fees considered in this research essentially shifted the incremental costs for road provision under traffic loading from the road provider to the road users. The purpose of this type of permit fee structure was to investigate road management policies that may be more cost effective when considering combined costs (road use and road provision costs). This type of permitting could provide a more direct linkage between road use and payment to fund road provision, which may be more equitable than current road funding mechanisms (e.g., gas tax, property tax). Model runs showed that the inclusion of permit fees incentivized road users for some OD pairs to change their routing and drive longer distances in order to drive larger percentages of their routes on upgraded road segments. This change in routing caused road user costs to increase with longer distances driven, and road provision costs to decrease due to lower traffic on gravel road segments. The shift in traffic routing due to the inclusion of permit fees was also found to change the road segments selected for upgrade, based on the simple traffic count prioritization upgrade criteria. While each considered scenario resulted in a net benefit (reduction in road provision and road use costs), the magnitude of the net benefit was consistently marginal in relation to the base case (without permit fees). Since permit fees were based on the incremental road provision cost, and, generally, road provision costs were small relative to road use costs, the magnitude of the permit fee does not impose strong incentives for altering road user behavior. Permit fees only altered road user route choice if there were alternative routes in which the road users did not have to significantly increase their trip distance (and costs) to find routes with upgraded road segments. Given the relatively low impact of permit fees on resulting combined costs found in the scenarios considered, the associated administrative costs may not be worthwhile for a road provider to implement such a permit fee structure. A sensitivity analysis was completed for select parameters of the model. The analysis provided insights into the selection of road provision parameters resulting in the lowest road provision and road use costs such as: minimum traffic levels used for road upgrade criteria, annual budget levels, and the impact of shifting traffic patterns. The model developed in this research illustrates the feasibility of using an ABM to support decision making involving road use and road provision policies. The complexities involved in road use, road provision and road performance required several simplifying assumptions to complete the model. Nonetheless, the results produced with the model illustrate the potential implications of various road use and road provision decisions. Further work to expand simplifying assumptions and refine model inputs may allow the model to become useful for road providers in understanding the impacts of alternative road provision policies for real world road networks

Commodity-based Freight Activity on Inland Waterways through the Fusion of Public Datasets for Multimodal Transportation Planning

Within the U.S., the 18.6 billion tons of goods currently moved along the multimodal transportation system are expected to grow 51% by 2045. Most of those goods are transported by roadways. However, several benefits can be realized by shippers and consumers by shifting freight to more efficient modes, such as inland waterways, or adopting a multimodal scheme. To support such freight growth sustainably and efficiently, federal legislation calls for the development of plans, methods, and tools to identify and prioritize future multimodal transportation infrastructure needs. However, given the historical mode-specific approach to freight data collection, analysis, and modeling, challenges remain to adopt a fully multimodal approach that integrates underrepresented modes, such as waterways, into multimodal forecasting tools to identify and prioritize transportation infrastructure needs. Examples of such challenges are data heterogeneity, confidentiality, limitations in terms of spatial and temporal coverage, high cost associated with data collection, subjectivity in surveys responses, etc. To overcome these challenges, this work fuses data across a variety of novel transportation sources to close existing gaps in freight data needed to support multimodal long-range freight planning. In particular, the objective of this work is to develop methods to allow integration of inland waterway transportation into commodity-based freight forecasting models, by leveraging Automatic Identification System (AIS) data. The following approaches are presented in this dissertation: i) Maritime Automatic Identification System (AIS) data is mapped to a detailed inland navigable waterway network, allowing for an improved representation of waterway modes into multimodal freight travel demand models which currently suffer from unbalanced representation of waterways. Validation results show the model correctly identifies 84% stops at inland waterway ports and 83.5% of trips crossing locks. ii) AIS and truck Global Positioning System (GPS) data are fused to a multimodal network to identify the area of impact of a freight investment, providing a single methodology and data source to compare and contrast diverse transportation infrastructure investments. This method identifies parallel truck and vessel flows indicating potential for modal shift. iii) Truck GPS and maritime Lock Performance Monitoring System (LPMS) data are fused via a multi-commodity assignment model to characterize and quantify annual commodity throughput at port terminals on inland waterways, generating new data from public datasets, to support estimation of commodity-based freight fluidity performance measures. Results show that 84% of ports had less than a 20% difference between estimated and observed truck volumes. iv) AIS, LPMS, and truck GPS datasets are fused to disaggregate estimated annual commodity port throughput to vessel trips on inland waterways. Vessel trips characterized by port of origin, destination, path, timestamp, and commodity carried, are mapped to a detailed inland waterway network, allowing for a detailed commodity flow analysis, previously unavailable in the public domain. The novel, repeatable, data-driven methods and models proposed in this work are applied to the 43 freight port terminals located on the Arkansas River. These models help to evaluate network performance, identify and prioritize multimodal freight transportation infrastructure needs, and introduce a unique focus on modal shift towards inland waterway transportation