Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

Untangling the Organizational Ambiguities in Supply Chain Risk Recognition, Assessment, and Response: The Role of Network Embeddedness

In this thesis, I focus on supply chain risk related ambiguity, which represents the ambiguities firms exhibit in recognizing, assessing, and responding to supply chain disruptions. I, primarily, argue that ambiguities associated with recognizing and responding to supply chain risk are information gathering and processing problems. Guided by the theoretical perspective of bounded rationality, I propose a typology of supply chain risk related ambiguity with four distinct dimensions. I, also, argue that the major contributor to risk related ambiguity is often the environment, specifically the web of suppliers. Hence, I focus on the characteristics of these supplier networks to examine the sources of ambiguity. I define three distinct elements of network embeddedness – relational, structural, and positional embeddedness – and argue that the ambiguity faced by a firm in appropriately identifying the nature or impacts of major disruptions is a function of these network properties. Based on a survey of large North American manufacturing firms, I found that the extent of the relational ties a firm has and its position in the network are significantly related to supply chain risk related ambiguity. However, this study did not provide any significant support for the hypothesized relationship between structural embeddedness and ambiguity. My research contributes towards the study of supply chain disruptions by using the idea of bounded rationality to understand supply chain risk related ambiguity and by providing evidence that the structure of supply chain networks influences the organizational understanding of and responses to supply chain disruptions.

Understanding Network Governance: A Case Study Exploration of Active Canada 20/20

Consistent with the governance shift towards network forms of governance, a number of new social movements have formed in response to the declining levels of physical activity in the Western world. One such movement is Active Canada 20/20: A Physical Activity Strategy and Change Agenda for Canada. Network governance is employed as the theoretical framework for this case study exploration of Active Canada 20/20 and the political landscape surrounding its development and implementation. Semi-structured interviews were conducted in addition to document/policy analysis and direct observations. Analysis of the data resulted in three overarching themes – the defining characteristics of network governance, the political landscape, and intersectoral linkages – that interconnect multifariously based the nature of the Canadian federal government and its relationship with the voluntary sector for physical activity. Despite progress in driving Active Canada 20/20 forward, entrenched dynamics of power need to be navigated within the political landscape surrounding network governance.

Identification of Network-Based Risk Factors Associated with Gonorrhea

The evolving antimicrobial resistance coupled with a recent increase in incidence highlights the importance of reducing gonococcal transmission. Establishing novel risk factors associated with gonorrhea facilitates the development of appropriate prevention and disease control strategies. Sexual Network Analysis (NA), a novel research technique used to further understand sexually transmitted infections, was used to identify network-based risk factors in a defined region in Ontario, Canada experiencing an increase in the incidence of gonorrhea. Linear network structures were identified as important reservoirs of gonococcal transmission. Additionally, a significant association between a central network position and gonorrhea was observed. The central participants were more likely to be younger, report a greater number of risk factors, engage in anonymous sex, have multiple sex partners in the past six months and have sex with the same sex. The network-based risk factors identified through sexual NA, serving as a method of analyzing local surveillance data, support the development of strategies aimed at reducing gonococcal spread.

Le financement des municipalités par le gouvernement fédéral au Canada et aux États-Unis: transferts et facteurs d'allocation.

Rapport de recherche

Fair Production and Allocation of an Excludable Nonrival Good

We study fairness in economies with one private good and one partially excludable nonrival good. A social ordering function determines for each profile of preferences an ordering of all conceivable allocations. We propose the following Free Lunch Aversion condition: if the private good contributions of two agents consuming the same quantity of the nonrival good have opposite signs, reducing that gap improves social welfare. This condition, combined with the more standard requirements of Unanimous Indifference and Responsiveness, delivers a form of welfare egalitarianism in which an agent's welfare at an allocation is measured by the quantity of the nonrival good that, consumed at no cost, would leave her indifferent to the bundle she is assigned.

Efficient Strategy-Proof Allocation Functions in Linear Production Economies

In a linear production model, we characterize the class of efficient and strategy-proof allocation functions, and the class of efficient and coalition strategy-proof allocation functions. In the former class, requiring equal treatment of equals allows us to identify a unique allocation function. This function is also the unique member of the latter class which satisfies uniform treatment of uniforms.

Resource-Monotonicity for House Allocation Problems

We study a simple model of assigning indivisible objects (e.g., houses, jobs, offices, etc.) to agents. Each agent receives at most one object and monetary compensations are not possible. We completely describe all rules satisfying efficiency and resource-monotonicity. The characterized rules assign the objects in a sequence of steps such that at each step there is either a dictator or two agents who “trade” objects from their hierarchically specified “endowments.”

Consistent House Allocation

In practice we often face the problem of assigning indivisible objects (e.g., schools, housing, jobs, offices) to agents (e.g., students, homeless, workers, professors) when monetary compensations are not possible. We show that a rule that satisfies consistency, strategy-proofness, and efficiency must be an efficient generalized priority rule; i.e. it must adapt to an acyclic priority structure, except -maybe- for up to three agents in each object's priority ordering.

Fair Allocation of Production Externalities: Recent Results

We survey recent axiomatic results in the theory of cost-sharing. In this litterature, a method computes the individual cost shares assigned to the users of a facility for any profile of demands and any monotonic cost function. We discuss two theories taking radically different views of the asymmetries of the cost function. In the full responsibility theory, each agent is accountable for the part of the costs that can be unambiguously separated and attributed to her own demand. In the partial responsibility theory, the asymmetries of the cost function have no bearing on individual cost shares, only the differences in demand levels matter. We describe several invariance and monotonicity properties that reflect both normative and strategic concerns. We uncover a number of logical trade-offs between our axioms, and derive axiomatic characterizations of a handful of intuitive methods: in the full responsibility approach, the Shapley-Shubik, Aumann-Shapley, and subsidyfree serial methods, and in the partial responsibility approach, the cross-subsidizing serial method and the family of quasi-proportional methods.

The Rebirth of a Communications Network: Europe at the Time of the Carolingians.

Rapport de recherche

Pour une allocation équitable des ressources en GMF

Objectif : Évaluer la « lourdeur » de la prise en charge clinique des personnes vivant avec le VIH/SIDA (PVVIH) afin d’ajuster l’allocation des ressources en GMF. Méthodologie : Analyse comparative entre le GMF de la Clinique médicale l’Actuel, les GMF montréalais et de l’ensemble du Québec, en identifiant les différences dans les profils de consommation de soins pour les années civiles 2006 à 2008 et les coûts d’utilisation des services pour l’année 2005. Résultats : En 2008, 78% de la clientèle inscrite au GMF de la Clinique médicale l’Actuel est vulnérable comparativement à 28% pour les autres GMF montréalais, une tendance observée pour l’ensemble du Québec. Le nombre moyen de visites par individu inscrit et vulnérable est de 7,57 au GMF l’Actuel alors que la moyenne montréalaise est de 3,37 et celle du Québec de 3,47. Enfin, le coût moyen des visites médicales au GMF l’Actuel en 2005 est de 203,93 $ comparativement à des coûts variant entre 132,14 et 149,53 $ pour les unités de comparaison. Conclusion : L’intensité de l’utilisation des ressources au GMF de la Clinique médicale l’Actuel (nombre d’individus vulnérables, nombre de visites et coûts) suggère que la prise en charge clinique des personnes vivant avec le VIH/SIDA est beaucoup plus lourde qu’un citoyen tout venant ou même de la majorité des autres catégories de vulnérabilité. Afin d’offrir un traitement juste et équitable aux GMF, l’inscription devrait être ajustée afin de tenir compte de la « lourdeur » de cette clientèle et valoriser la prise en charge des personnes qui présentent des tableaux cliniques complexes.

Models and algorithms for transit network planning.

Tesis (Doctor en Ingeniería con Especialidad en Ingeniería de Sistemas) UANL, 2012.