Cooperative Multi-robot Patrolling: A study of distributed approaches based on mathematical models of game theory to protect infrastructures

El principio de Teoría de Juegos permite desarrollar modelos estocásticos de patrullaje multi-robot para proteger infraestructuras criticas. La protección de infraestructuras criticas representa un gran reto para los países al rededor del mundo, principalmente después de los ataques terroristas llevados a cabo la década pasada. En este documento el termino infraestructura hace referencia a aeropuertos, plantas nucleares u otros instalaciones. El problema de patrullaje se define como la actividad de patrullar un entorno determinado para monitorear cualquier actividad o sensar algunas variables ambientales. En esta actividad, un grupo de robots debe visitar un conjunto de puntos de interés definidos en un entorno en intervalos de tiempo irregulares con propósitos de seguridad. Los modelos de partullaje multi-robot son utilizados para resolver este problema. Hasta el momento existen trabajos que resuelven este problema utilizando diversos principios matemáticos. Los modelos de patrullaje multi-robot desarrollados en esos trabajos representan un gran avance en este campo de investigación. Sin embargo, los modelos con los mejores resultados no son viables para aplicaciones de seguridad debido a su naturaleza centralizada y determinista. Esta tesis presenta cinco modelos de patrullaje multi-robot distribuidos e impredecibles basados en modelos matemáticos de aprendizaje de Teoría de Juegos. El objetivo del desarrollo de estos modelos está en resolver los inconvenientes presentes en trabajos preliminares. Con esta finalidad, el problema de patrullaje multi-robot se formuló utilizando conceptos de Teoría de Grafos, en la cual se definieron varios juegos en cada vértice de un grafo. Los modelos de patrullaje multi-robot desarrollados en este trabajo de investigación se han validado y comparado con los mejores modelos disponibles en la literatura. Para llevar a cabo tanto la validación como la comparación se ha utilizado un simulador de patrullaje y un grupo de robots reales. Los resultados experimentales muestran que los modelos de patrullaje desarrollados en este trabajo de investigación trabajan mejor que modelos de trabajos previos en el 80% de 150 casos de estudio. Además de esto, estos modelos cuentan con varias características importantes tales como distribución, robustez, escalabilidad y dinamismo. Los avances logrados con este trabajo de investigación dan evidencia del potencial de Teoría de Juegos para desarrollar modelos de patrullaje útiles para proteger infraestructuras. ABSTRACT Game theory principle allows to developing stochastic multi-robot patrolling models to protect critical infrastructures. Critical infrastructures protection is a great concern for countries around the world, mainly due to terrorist attacks in the last decade. In this document, the term infrastructures includes airports, nuclear power plants, and many other facilities. The patrolling problem is defined as the activity of traversing a given environment to monitoring any activity or sensing some environmental variables If this activity were performed by a fleet of robots, they would have to visit some places of interest of an environment at irregular intervals of time for security purposes. This problem is solved using multi-robot patrolling models. To date, literature works have been solved this problem applying various mathematical principles.The multi-robot patrolling models developed in those works represent great advances in this field. However, the models that obtain the best results are unfeasible for security applications due to their centralized and predictable nature. This thesis presents five distributed and unpredictable multi-robot patrolling models based on mathematical learning models derived from Game Theory. These multi-robot patrolling models aim at overcoming the disadvantages of previous work. To this end, the multi-robot patrolling problem was formulated using concepts of Graph Theory to represent the environment. Several normal-form games were defined at each vertex of a graph in this formulation. The multi-robot patrolling models developed in this research work have been validated and compared with best ranked multi-robot patrolling models in the literature. Both validation and comparison were preformed by using both a patrolling simulator and real robots. Experimental results show that the multirobot patrolling models developed in this research work improve previous ones in as many as 80% of 150 cases of study. Moreover, these multi-robot patrolling models rely on several features to highlight in security applications such as distribution, robustness, scalability, and dynamism. The achievements obtained in this research work validate the potential of Game Theory to develop patrolling models to protect infrastructures.

A management model for closed-loop supply chains of reusable articles

This PhD dissertation is framed in the emergent fields of Reverse Logistics and ClosedLoop Supply Chain (CLSC) management. This subarea of supply chain management has gained researchers and practitioners' attention over the last 15 years to become a fully recognized subdiscipline of the Operations Management field. More specifically, among all the activities that are included within the CLSC area, the focus of this dissertation is centered in direct reuse aspects. The main contribution of this dissertation to current knowledge is twofold. First, a framework for the so-called reuse CLSC is developed. This conceptual model is grounded in a set of six case studies conducted by the author in real industrial settings. The model has also been contrasted with existing literature and with academic and professional experts on the topic as well. The framework encompasses four building blocks. In the first block, a typology for reusable articles is put forward, distinguishing between Returnable Transport Items (RTI), Reusable Packaging Materials (RPM), and Reusable Products (RP). In the second block, the common characteristics that render reuse CLSC difficult to manage from a logistical standpoint are identified, namely: fleet shrinkage, significant investment and limited visibility. In the third block, the main problems arising in the management of reuse CLSC are analyzed, such as: (1) define fleet size dimension, (2) control cycle time and promote articles rotation, (3) control return rate and prevent shrinkage, (4) define purchase policies for new articles, (5) plan and control reconditioning activities, and (6) balance inventory between depots. Finally, in the fourth block some solutions to those issues are developed. Firstly, problems (2) and (3) are addressed through the comparative analysis of alternative strategies for controlling cycle time and return rate. Secondly, a methodology for calculating the required fleet size is elaborated (problem (1)). This methodology is valid for different configurations of the physical flows in the reuse CLSC. Likewise, some directions are pointed out for further development of a similar method for defining purchase policies for new articles (problem (4)). The second main contribution of this dissertation is embedded in the solutions part (block 4) of the conceptual framework and comprises a two-level decision problem integrating two mixed integer linear programming (MILP) models that have been formulated and solved to optimality using AIMMS as modeling language, CPLEX as solver and Excel spreadsheet for data introduction and output presentation. The results obtained are analyzed in order to measure in a client-supplier system the economic impact of two alternative control strategies (recovery policies) in the context of reuse. In addition, the models support decision-making regarding the selection of the appropriate recovery policy against the characteristics of demand pattern and the structure of the relevant costs in the system. The triangulation of methods used in this thesis has enabled to address the same research topic with different approaches and thus, the robustness of the results obtained is strengthened.