This paper presents a microsimulation model of the rental sector in the Greater Toronto (GTA). The main contributions of this research are that it develops a conceptual framework for modeling housing issues and policies, and implements a rental model within the Integrated Land Use, Transport, and Environment (ILUTE) framework developed at the University of Toronto. The key components of the rental model include: (1) the production of rental units; (2) a tenure choice model; (3) a rent setting model; and (4) a rental market model. The rental model is simulated yearly from 1986 till 2006. The preliminary results are presented for the number of households renting, the average rent per census tract, and the number of renter households facing affordability issues. Two areas of future research are proposed that seek: (1) to improve the current model’s accuracy; and (2) to develop a more dynamic model.

In this thesis, we generalize a set of facility location models within a two-stage robust optimization framework by assuming each demand is only known to lie within a continuous and bounded uncertainty region. Our approach involves discretizing each uncertainty region into a set of finite scenarios, each of which represents a potential location where the demand may be realized. We show that the gap between the optimal values of the theorized continuous uncertainty problem and our discretized model can be bounded by a function of the granularity of the discretization. We then propose a solution technique based on row-and-column generation, and compare its performance with existing solution methods. Lastly, we apply our robust location models to the problem of ambulance positioning using cardiac arrest location data from the City of Toronto, and show that hedging against demand location uncertainty may help decrease EMS response times to cardiac arrest emergencies.

In this thesis, we generalize a set of facility location models within a two-stage robust optimization framework by assuming each demand is only known to lie within a continuous and bounded uncertainty region. Our approach involves discretizing each uncertainty region into a set of finite scenarios, each of which represents a potential location where the demand may be realized. We show that the gap between the optimal values of the theorized continuous uncertainty problem and our discretized model can be bounded by a function of the granularity of the discretization. We then propose a solution technique based on row-and-column generation, and compare its performance with existing solution methods. Lastly, we apply our robust location models to the problem of ambulance positioning using cardiac arrest location data from the City of Toronto, and show that hedging against demand location uncertainty may help decrease EMS response times to cardiac arrest emergencies.

The Web has become an open decentralized global information / knowledge repository, a platform for distributed computing and global electronic markets, where people are confronted with information of unknown sources, and need to interact with “strangers”. This makes trust and the validity of information in cyberspace arise as crucial issues. This thesis proposes knowledge provenance (KP) as a formal approach to determining the origin and validity of information / knowledge on the Web, by means of modeling and maintaining the information sources, information dependencies, and trust structures. We conceptualize and axiomatize KP ontology including static KP and dynamic KP. The proposed KP ontology, provides a formal representation of linking trust in information creators and belief in the information created; lays a foundation for further study of knowledge provenance; provides logical systems for provenance reasoning by machines. The web ontology of KP can be used to annotate web information; and KP reasoner can be used as a tool to trace the origin and to determine the validity of Web information. Since knowledge provenance is based on trust in information sources, this thesis also proposes a logical theory of trust in epistemic logic and situation calculus. In particular, we formally define the semantics of trust; from it, we identify two types of trust: trust in belief and trust in performance; reveal and prove that trust in belief is transitive; trust in performance is not, but by trust in belief, trust in performance can propagate in social networks; by using situation calculus in trust formalization, the context of trust is formally represented by reified fluents; we also propose a distributed logical model for trust reasoning using social networks, by which each agent’s private data about trust relationships can be protected. This study provides a formal theoretical analysis on the transitivity of trust, which supports trust propagation in social networks. This study of trust supports not only knowledge provenance but also the general trust modeling in cyberspace.

Procedures are standardized lists of instructions that designate the safe and accepted way of accomplishing a task. This study intended to develop and compare the usability of paper-based industrial operating procedures. Two procedures at a plant were redesigned with evidence-based guidelines and human factors input. 16 operators of varying experience were asked to read through and assess the new and old procedures. The new procedures were rated significantly or moderately better than their predecessors for efficiency, effectiveness, and subjective satisfaction. On average, inexperienced operators reported fewer inaccuracies, more confusion, and higher workload ratings than their experienced counterparts, regardless of procedure type or area. For satisfaction, experienced and inexperienced operators reported similar ratings across both procedure types and areas. Future studies should attempt to discern which particular change in the procedures contributed the most to increased usability, and whether operator experience significantly correlates with usability ratings.

Procedures are standardized lists of instructions that designate the safe and accepted way of accomplishing a task. This study intended to develop and compare the usability of paper-based industrial operating procedures. Two procedures at a plant were redesigned with evidence-based guidelines and human factors input. 16 operators of varying experience were asked to read through and assess the new and old procedures. The new procedures were rated significantly or moderately better than their predecessors for efficiency, effectiveness, and subjective satisfaction. On average, inexperienced operators reported fewer inaccuracies, more confusion, and higher workload ratings than their experienced counterparts, regardless of procedure type or area. For satisfaction, experienced and inexperienced operators reported similar ratings across both procedure types and areas. Future studies should attempt to discern which particular change in the procedures contributed the most to increased usability, and whether operator experience significantly correlates with usability ratings.

Reasoning about processes in applications such as manufacturing, web services, enterprise modeling, and planning requires the representation of composite processes with complicated flows of control. Previous research in process representation has used formalisms such as Event Systems, Petri nets, and the Unified Modeling Language activity diagrams. The computational hardness of temporal projection problems in Event Systems has been extensively examined in the literature, whereas Petri nets and UML activity diagrams are applied to describe more elaborate processes. This thesis takes a systematic look into the temporal reasoning problems in Event Systems and assigns accurate semantics to both Petri nets and, for the first time, to UML activity diagrams. We give an analysis of computational complexity in temporal projection problems by exploring the boundary between their tractable and intractable subproblems. Our results provide new insights into the prominent role the properties of partial ordering play, however we also show that partial ordering is not the sole source of the intractability as has been claimed in an earlier work by Nebel and B{\"a}ckstr{\"o}m. Two influential modeling languages, Petri nets and UML activity diagrams, are axiomatized as two Basic Action Theories of Situation Calculus. They are called, respectively, SCOPE (Situation Calculus Ontology of PEtri nets) and SCAD (Situation Calculus theory of Activity Diagrams). We provide a Prolog implementation of SCOPE and prove the correctness of this program for regressable queries. We use SCAD to axiomatize the structural and dynamic properties of UML activity diagrams and also provide the first set of computational results with regard to the reachability problems in activity diagrams. The correctness of each of these two axiomatizations is also demonstrated by proving that the theory is satisfiable, and the intended interpretation corresponds to a model of the theory.

Reducing emergency department (ED) wait times are a major priority for the Ontario Government. Overcrowded EDs, cumulative effects of the delays in hospital processes and lack of resources are manifested in the phenomenon of long wait times. This thesis aims to estimate in real-time, a minimum wait time confidence interval for urgent abdominal pain patients on weekdays based on ED operations, waiting room status and ED census indicators through multivariate backwards stepwise regression modeling. The ED wait times model accurately predicted a 95% wait time confidence interval for patients. Common underlying factors attributed to long wait times include the total number of emergent and urgent patients in the waiting room, the total number of patient waiting for a consultation and the number of patients not seen within the Ontario Government’s target times. This information is useful in managing patient expectations and appropriately allocating resources to improve wait times.

The goal of this dissertation is to understand the market-based mechanisms that enable shippers to allocate lanes in an efficient way for truckload (TL) transportation procurement despite the self-interest of carriers. To understand the market-based mechanisms, we focus on proposing some novel models and mechanisms to enhance the use of combinatorial auction for TL transportation procurement. In this dissertation, our approach to gaining the understanding consists of three parts: 1. We develop a carrier optimal bid generation model for carriers (bidders) to discover the best sets of lanes to bid for at a given round. The optimal bid generation model simultaneously generates alternative tours and selects the most profitable package bid for the carrier under a myopic strategy, which has never been considered before. The simultaneous tour generation and selection significantly lessen the computational complexities of a carrier's optimization problem since it is unnecessary for the carrier to calculate the values for all possible packages. 2. We present an iterative combinatorial auction design that integrates the optimization problems for both the shipper and the bidders where the approximate dual prices derived from the result of a winner determination solution are used by the bidders in identifying profitable lanes. The auctions also allow the bidders to submit exclusive-OR (XOR) bids and are able to deal with some common business considerations. The extension of the concept of active bids enables this mechanism to effectively mitigate the exposure problem, the threshold problem, and the free-riding problem. Furthermore, both the shippers and the carriers are better off compared to multi-round auctions that do not integrate the shippers' and carriers' optimizations. 3. We extend a deterministic winner determination model to a two-stage stochastic winner determination model for TL transportation procurement under shipment volume uncertainty. We demonstrate that the value of the stochastic solution is always at least as good as one obtained by a deterministic model based on using expected shipment volumes. The sWDP model is to the best of our knowledge the first winner determination formulation of any kind that explicitly incorporates demand uncertainty.

Reasoning about processes in applications such as manufacturing, web services, enterprise modeling, and planning requires the representation of composite processes with complicated flows of control. Previous research in process representation has used formalisms such as Event Systems, Petri nets, and the Unified Modeling Language activity diagrams. The computational hardness of temporal projection problems in Event Systems has been extensively examined in the literature, whereas Petri nets and UML activity diagrams are applied to describe more elaborate processes. This thesis takes a systematic look into the temporal reasoning problems in Event Systems and assigns accurate semantics to both Petri nets and, for the first time, to UML activity diagrams. We give an analysis of computational complexity in temporal projection problems by exploring the boundary between their tractable and intractable subproblems. Our results provide new insights into the prominent role the properties of partial ordering play, however we also show that partial ordering is not the sole source of the intractability as has been claimed in an earlier work by Nebel and B{\"a}ckstr{\"o}m. Two influential modeling languages, Petri nets and UML activity diagrams, are axiomatized as two Basic Action Theories of Situation Calculus. They are called, respectively, SCOPE (Situation Calculus Ontology of PEtri nets) and SCAD (Situation Calculus theory of Activity Diagrams). We provide a Prolog implementation of SCOPE and prove the correctness of this program for regressable queries. We use SCAD to axiomatize the structural and dynamic properties of UML activity diagrams and also provide the first set of computational results with regard to the reachability problems in activity diagrams. The correctness of each of these two axiomatizations is also demonstrated by proving that the theory is satisfiable, and the intended interpretation corresponds to a model of the theory.