Date of Award

7-7-2020

Publication Type

Master Thesis

Degree Name

M.A.Sc.

Department

Civil and Environmental Engineering

First Advisor

Hanna Maoh

Keywords

GIS (Geographic Information System), Location-Allocation Modeling, Logistics Facility, Multi-Criteria Decision Analysis (MCDA), P-Median Problem, Raster Data Analysis

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Abstract

Freight transportation plays a major role in determining the economic health of a region. Efficient freight transportation systems are typically associated with reducing the cost of moving goods from and to logistics facilities. Understanding the clustering pattern of truck trip ends (i.e., productions and attractions) can help optimize the location of such facilities over space. This thesis explores freight activities, using data from a large sample of trucks owned by Canadian carriers for the month of September 2014, to propose ways to optimize the location of future logistics facilities in Ontario. Heat maps using the kernel density estimation method are generated to highlight the clustering of these trips by industry. Besides the exploratory work, multi-criteria decision analysis is performed to create a suitability surface to identify potential locations where new logistics facilities could be established. A total of 18 potential locations across Ontario are identified and used to execute a number of location-allocation scenarios. The ArcGIS 10.6 software and its extensions (namely Spatial Analyst and Network Analyst) are heavily utilized in the analysis to create the kernel density maps, suitability surface, and the Location-Allocation modeling work. The results indicate that Hamilton, Ontario would be the most optimal location for establishing a future logistics facility to complement the operations occurring in the Peel region. When factoring the Canada-US border, Windsor, Ontario can be considered the second most optimal location after Hamilton. The conducted analysis allows us to see the optimized locations for new logistics facilities to service local markets around Ontario as well as US markets serviced by the Ontario-US land border crossings.

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