Braess' paradox is a counter-intuitive phenomenon which can occur in congesting networks. It refers to those cases where the introduction of a new link in the network results in the total travel time on the network increasing. The dissertation starts by introducing the traffic assignment problem and the concept of equilibrium in traffic assignment. The concept of equilibrium is based on Wardrop's first principle that all travellers will attempt to minimize their own travel time regardless of the effect on others. A literature review includes details of a number of papers that have been published investigating theoretical aspects of the paradox. There is also a brief description of Game Theory and the Nash Equilibrium. It has been shown that the equilibrium assignment is an example of Nash Equilibrium. The majority of work that has been published deals with networks where the delay functions that are used to compute the travel times on the links of the network do not include explicit representation of the capacity of the links. In this dissertation a network that is similar in form to the one first presented by Braess was constructed with the difference being that the well-known BPR function was used in the delay functions. This network was used to show that a number of findings that had been presented previously using simpler functions also applied to this network. It was shown that when it occurs, Braess' paradox only occurs over a range of values at relatively low levels of congestion. Real-world networks were then investigated and it was found that similar results occurred to those found in the simpler test networks that are often used in discussions of the paradox. Two methodologies of eliminating the paradox were investigated and the results are presented. / Decision Sciences / M.Sc.

Braess' paradox is a counter-intuitive phenomenon which can occur in congesting networks. It refers to those cases where the introduction of a new link in the network results in the total travel time on the network increasing. The dissertation starts by introducing the traffic assignment problem and the concept of equilibrium in traffic assignment. The concept of equilibrium is based on Wardrop's first principle that all travellers will attempt to minimize their own travel time regardless of the effect on others. A literature review includes details of a number of papers that have been published investigating theoretical aspects of the paradox. There is also a brief description of Game Theory and the Nash Equilibrium. It has been shown that the equilibrium assignment is an example of Nash Equilibrium. The majority of work that has been published deals with networks where the delay functions that are used to compute the travel times on the links of the network do not include explicit representation of the capacity of the links. In this dissertation a network that is similar in form to the one first presented by Braess was constructed with the difference being that the well-known BPR function was used in the delay functions. This network was used to show that a number of findings that had been presented previously using simpler functions also applied to this network. It was shown that when it occurs, Braess' paradox only occurs over a range of values at relatively low levels of congestion. Real-world networks were then investigated and it was found that similar results occurred to those found in the simpler test networks that are often used in discussions of the paradox. Two methodologies of eliminating the paradox were investigated and the results are presented. / Decision Sciences / M.Sc.

abstract: This research develops heuristics to manage both mandatory and optional network capacity reductions to better serve the network flows. The main application discussed relates to transportation networks, and flow cost relates to travel cost of users of the network. Temporary mandatory capacity reductions are required by maintenance activities. The objective of managing maintenance activities and the attendant temporary network capacity reductions is to schedule the required segment closures so that all maintenance work can be completed on time, and the total flow cost over the maintenance period is minimized for different types of flows. The goal of optional network capacity reduction is to selectively reduce the capacity of some links to improve the overall efficiency of user-optimized flows, where each traveler takes the route that minimizes the traveler’s trip cost. In this dissertation, both managing mandatory and optional network capacity reductions are addressed with the consideration of network-wide flow diversions due to changed link capacities. This research first investigates the maintenance scheduling in transportation networks with service vehicles (e.g., truck fleets and passenger transport fleets), where these vehicles are assumed to take the system-optimized routes that minimize the total travel cost of the fleet. This problem is solved with the randomized fixed-and-optimize heuristic developed. This research also investigates the maintenance scheduling in networks with multi-modal traffic that consists of (1) regular human-driven cars with user-optimized routing and (2) self-driving vehicles with system-optimized routing. An iterative mixed flow assignment algorithm is developed to obtain the multi-modal traffic assignment resulting from a maintenance schedule. The genetic algorithm with multi-point crossover is applied to obtain a good schedule. Based on the Braess’ paradox that removing some links may alleviate the congestion of user-optimized flows, this research generalizes the Braess’ paradox to reduce the capacity of selected links to improve the efficiency of the resultant user-optimized flows. A heuristic is developed to identify links to reduce capacity, and the corresponding capacity reduction amounts, to get more efficient total flows. Experiments on real networks demonstrate the generalized Braess’ paradox exists in reality, and the heuristic developed solves real-world test cases even when commercial solvers fail. / Dissertation/Thesis / Doctoral Dissertation Industrial Engineering 2017

The Braess Paradox is a rare phenomenon that only occurs under specific scenarios. This project aims to study the probability of the Braess Paradox occurring in a Directed Weighted Graph while the number of edges increases. The graphs in the experiment are focused on studying the occurrence of the Braess Paradox in a directed weighted scale-free network while transforming it into a directed weighted complete graph. A simulation model is used to simulate the bots traveling through a network to detect the occurrence of the Braess Paradox, considering the increase of directed weighted edges. A Graph Neural Network (GNN) is later used to train on the data produced by the simulation model.