Estudio de propiedades de repartos con optimización de bienestar social igualitario

Durante mucho tiempo, el área de la economía ha sido un campo con un notable crecimiento que no se ha visto afectado por las nuevas tecnologías hasta hace unas pocas décadas. Con el auge de las ciencias de la computación, la economía ha sufrido notables cambios en todos sus aspectos. Uno de ellos es el de realizar repartos de recursos de la manera más eficiente posible. Abordar este tipo de problemas antes de la aparición de la computación moderna era una tarea enormemente lenta y costosa en tiempo, pero hoy en día es posible desarrollar pruebas altamente eficientes que permitan averiguar cómo se realizan estos repartos de recursos bajo unas determinadas reglas impuestas de antemano. A lo largo de esta memoria exploraremos un modelo concreto de reparto de recursos y estudiaremos diferentes tipos de experimentos que analizaremos y sobre los que obtendremos conclusiones que nos permiten saber cómo se comportan este tipo de problemas

An agent-based approach to intelligent manufacturing network configuration

The participation of small and medium enterprises in inter-firm collaboration can enhance their market reach while maintaining production lean. The conventional centralised collaboration approach is believed to be unsustainable, in today’s complex environment. The research aimed to investigate manufacturing network collaborations, where manufacturers maintain control over their scheduling activities and participate in a market-based event, to decide which collaborations are retained. The work investigated two pairing mechanisms where the intention was to capture and optimise collaboration at the granular level and then build up a network from those intermediate forms of organisation. The research also looked at two bidding protocols. The first protocol involves manufacturers that bid for operations from the process plan of a job. The second protocol is concerned with networks that bid for a job in its entirety. The problem, defined by an industrial use case and operation research data sets, was modelled as decentralised flow shop scheduling. The holonic paradigm identified the problem solving agents that participated in agent-based modelling and simulation of the pairing and the bidding protocols. The protocols are strongly believed to achieve true decentralisation of scheduling, with good performance on scalability, conflict resolution and schedule optimisation, for the purpose of inter-firm collaboration

A Framework for Resource Allocation in Time Critical Dynamic Environments Based on Social Welfare and Local Search and its Application to Healthcare

This thesis provides an artificial intelligence approach for the problem of resource allocation in time-critical dynamic environments. Motivated by healthcare scenarios such as mass casualty incidents, we are concerned with making effective decisions about allocating to patients the limited resources of ambulances, doctors and other medical staff members, in real-time, under changing circumstances. We cover two distinct stages: the Ambulance stage (at the location of the incident) and the Hospital stage (where the patient requires treatment). Our work addresses both determining the best allocation and supporting decision making (for medical staff to explore possible options). Our approach uses local search with social welfare functions in order to find the best allocations, making use of a centralized tracking of patients and resources. We also clarify how sensing can assist in updating the central system with new information. A key concept in our solution is that of a policy that attempts to minimize cost and maximize utility. To confirm the value of our approach, we present a series of detailed simulations of ambulance and hospital scenarios, and compare algorithms with competing principles of allocation (e.g. sickest first) and societal preferences (e.g. egalitarian allotment). In all, we offer a novel direction for resource allocation that is principled and that offers quantifiable feedback for professionals who are engaged in making resource allocation decisions