Electricity Markets Portfolio Optimization using a Particle Swarm Approach

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.

A systematic methodology to analyse the performance and design configurations of business interoperability in cooperative industrial networks

This thesis proposes a methodology for modelling business interoperability in a context of cooperative industrial networks. The purpose is to develop a methodology that enables the design of cooperative industrial network platforms that are able to deliver business interoperability and the analysis of its impact on the performance of these platforms. To achieve the proposed objective, two modelling tools have been employed: the Axiomatic Design Theory for the design of interoperable platforms; and Agent-Based Simulation for the analysis of the impact of business interoperability. The sequence of the application of the two modelling tools depends on the scenario under analysis, i.e. whether the cooperative industrial network platform exists or not. If the cooperative industrial network platform does not exist, the methodology suggests first the application of the Axiomatic Design Theory to design different configurations of interoperable cooperative industrial network platforms, and then the use of Agent-Based Simulation to analyse or predict the business interoperability and operational performance of the designed configurations. Otherwise, one should start by analysing the performance of the existing platform and based on the achieved results, decide whether it is necessary to redesign it or not. If the redesign is needed, simulation is once again used to predict the performance of the redesigned platform. To explain how those two modelling tools can be applied in practice, a theoretical modelling framework, a theoretical Axiomatic Design model and a theoretical Agent-Based Simulation model are proposed. To demonstrate the applicability of the proposed methodology and/or to validate the proposed theoretical models, a case study regarding a Portuguese Reverse Logistics cooperative network (Valorpneu network) and a case study regarding a Portuguese construction project (Dam Baixo Sabor network) are presented. The findings of the application of the proposed methodology to these two case studies suggest that indeed the Axiomatic Design Theory can effectively contribute in the design of interoperable cooperative industrial network platforms and that Agent-Based Simulation provides an effective set of tools for analysing the impact of business interoperability on the performance of those platforms. However, these conclusions cannot be generalised as only two case studies have been carried out. In terms of relevance to theory, this is the first time that the network effect is addressed in the analysis of the impact of business interoperability on the performance of networked companies and also the first time that a holistic approach is proposed to design interoperable cooperative industrial network platforms. Regarding the practical implications, the proposed methodology is intended to provide industrial managers a management tool that can guide them easily, and in practical and systematic way, in the design of configurations of interoperable cooperative industrial network platforms and/or in the analysis of the impact of business interoperability on the performance of their companies and the networks where their companies operate.

Plataforma per a la simulació de xarxes de sensors

Aquest projecte descriu una plataforma de simulació per a xarxes de sensors des de la perspectiva dels sistemes multi-agents. La plataforma s'ha dissenyat per facilitar la simulació de diferents aplicacions concretes de xarxes de sensors. A més, s'ha entregat com a artefacte del projecte IEA (Institucions Electròniques Autònomes, TIN2006-15662-C02-0) de l'IIIACSIC. Dins l'entorn de l'IEA, aquesta és l'eina que aporta les capacitats de simulació per donar suport al disseny d'algorismes adaptatius per a xarxes de sensors.

Transition to parenthood: The role of social interaction and endogenous networks

Empirical studies indicate that the transition to parenthood is influenced by an individual's peer group. To study the mechanisms creating interdepen- dencies across individuals' transition to parenthood and its timing we apply an agent-based simulation model. We build a one-sex model and provide agents with three different characteristics regarding age, intended education and parity. Agents endogenously form their network based on social closeness. Network members then may influence the agents' transition to higher parity levels. Our numerical simulations indicate that accounting for social inter- actions can explain the shift of first-birth probabilities in Austria over the period 1984 to 2004. Moreover, we apply our model to forecast age-specific fertility rates up to 2016.

Evaluación de la efectividad de una organización en el campo de percepción de marca usando un sistema de simulación computarizado basado en agentes

El presente proyecto de investigación tiene como objetivo general evaluar la efectividad de los esfuerzos de una unidad de negocio particular de la compañía Novartis de Colombia S.A. en el área de la percepción de marca mediante un sistema de simulación que implementa una metodología para la medición de esta última. Se tiene en cuenta que contar con datos exactos acerca de cómo los clientes finales perciben una marca es un tarea dispendiosa y que aún no tiene una fórmula matemática, por lo tanto, es muy subjetivo el proceso de entender a los consumidores por parte de los directivos de la empresa. El proceso planea que por medio del procedimiento planteado que se basa en una simulación por computador y más concretamente con una modelación basada en agentes se permita acercar a las partes involucradas en el proceso de compra, es decir, la empresa involucrada, vendedores, clientes y finalmente clientes potenciales.

Evaluación de la efectividad de la marca LG en el ámbito de la percepción de marca usando una herramienta de simulación computacional

Cuando las empresas evalúan los resultados de su planeación estratégica y de mercadeo se enfrentan en numerosas ocasiones al escepticismo sobre cómo dicha planeación favoreció o afectó la percepción hacia la empresa y sus productos. Este proyecto propone por medio del uso de una herramienta de simulación computacional reducir el factor de incertidumbre de LG Electronics en el valor percibido de marca por la población de Bogotá D.C. en cada una de sus líneas de producto; el grado de inversión en mercadeo, publicidad, distribución y servicio. Para ello los consumidores son modelados como agentes inteligentes con poder de recomendación, quienes se basan principalmente en la experiencia generada por el producto y en el grado de influencia de las estrategias de mercadeo que afectan su decisión de compra, de preferencia y de permanencia. Adicionalmente se mide la retribución en utilidades y en recordación de marca de las inversiones en mercadeo que la compañía realiza.

Evaluación de la efectividad de la marca “Arroz Don Cabe” en el ámbito de la percepción de marca usando una herramienta de simulación computacional

Al hacer la evaluación de los resultados asociados con procesos de planeación estratégica y mercadeo en las empresas, la dirección enfrenta un cierto nivel de incertidumbre al no saber si estos planes afectaron positiva o negativamente la posición de la empresa en su entorno. El presente trabajo hace uso de una herramienta de simulación basada en agentes inteligentes para reducir el mencionado factor de incertidumbre, en este caso, para la empresa Corgranos S.A. Se espera modelar el comportamiento de los grupos poblacionales directa e indirectamente involucrados con la empresa para así afinar los esfuerzos que se efectúan sobre cada uno de ellos, siendo la diferencia entre las suposiciones iniciales y los resultados de la simulación el verdadero aporte del trabajo.

Evaluación de la efectividad de una organización en el campo de percepción de marca usando un sistema de simulación computarizado basado en agentes

El presente proyecto de investigación tiene como objetivo general evaluar la efectividad de los esfuerzos en la percepción de una marca a través de la compañía “Distr & Co.” en Colombia, teniendo como fuente principal un sistema de simulación basado en agentes inteligentes; con el que se busca mejorar la metodología para medir el desempeño de una marca dada. El proceso plantea que por medio de la modelación basada en agentes se pueda dar acercamiento a las partes involucradas en los procesos de compra, es decir, la empresa, vendedores, clientes y finalmente clientes potenciales.

Estado situacional de los modelos basados en agentes y su impacto en la investigación organizacional

En un mundo hiperconectado, dinámico y cargado de incertidumbre como el actual, los métodos y modelos analíticos convencionales están mostrando sus limitaciones. Las organizaciones requieren, por tanto, herramientas útiles que empleen tecnología de información y modelos de simulación computacional como mecanismos para la toma de decisiones y la resolución de problemas. Una de las más recientes, potentes y prometedoras es el modelamiento y la simulación basados en agentes (MSBA). Muchas organizaciones, incluidas empresas consultoras, emplean esta técnica para comprender fenómenos, hacer evaluación de estrategias y resolver problemas de diversa índole. Pese a ello, no existe (hasta donde conocemos) un estado situacional acerca del MSBA y su aplicación a la investigación organizacional. Cabe anotar, además, que por su novedad no es un tema suficientemente difundido y trabajado en Latinoamérica. En consecuencia, este proyecto pretende elaborar un estado situacional sobre el MSBA y su impacto sobre la investigación organizacional.

Evaluación de la efectividad de la marca Bodytech® en el ámbito de la percepción de marca haciendo uso de una herramienta de simulación computacional

El presente trabajo de investigación fue realizado con el propósito de modelar el proceso de percepción de marca a partir del análisis de los componentes provenientes de la marca “Bodytech”, esto con el fin de simular el proceso de percepción de marca y evaluar la efectividad de la misma. El proceso que se modela es el de percepción – razonamiento – acción y se hace con el fin de evaluar los gastos en cada uno de los “componentes” que antes mencionaron Para realizar el análisis se hizo uso de un sistema de simulación basada en agentes, el cual recibe valores de diferentes variables analizadas por medio de tres herramientas: (1) un diagrama de grupos poblacionales, (2) un diagrama de desagregación de los núcleos temáticos de la marca y (3) las conclusiones obtenidas de una entrevista que se realizó a los responsables de gestionar la marca. Dicho proceso se lleva a cabo con el fin de poder determinar los valores relacionados al gasto en cada uno de los núcleos temáticos que llevan al sistema a evaluar la percepción de marca y la efectividad de estos gastos. Posteriormente, basados en los resultados del sistema de simulación, se obtiene un escenario que puede ser entendido y parcialmente predicho que le permitirán a Bodytech tener una herramienta de valoración de percepción de su marca.

Agentes Inteligentes com Foco de Atenção Afetivo em Simulações Baseadas em Agentes

Simulations based on cognitively rich agents can become a very intensive computing task, especially when the simulated environment represents a complex system. This situation becomes worse when time constraints are present. This kind of simulations would benefit from a mechanism that improves the way agents perceive and react to changes in these types of environments. In other worlds, an approach to improve the efficiency (performance and accuracy) in the decision process of autonomous agents in a simulation would be useful. In complex environments, and full of variables, it is possible that not every information available to the agent is necessary for its decision-making process, depending indeed, on the task being performed. Then, the agent would need to filter the coming perceptions in the same as we do with our attentions focus. By using a focus of attention, only the information that really matters to the agent running context are perceived (cognitively processed), which can improve the decision making process. The architecture proposed herein presents a structure for cognitive agents divided into two parts: 1) the main part contains the reasoning / planning process, knowledge and affective state of the agent, and 2) a set of behaviors that are triggered by planning in order to achieve the agent s goals. Each of these behaviors has a runtime dynamically adjustable focus of attention, adjusted according to the variation of the agent s affective state. The focus of each behavior is divided into a qualitative focus, which is responsible for the quality of the perceived data, and a quantitative focus, which is responsible for the quantity of the perceived data. Thus, the behavior will be able to filter the information sent by the agent sensors, and build a list of perceived elements containing only the information necessary to the agent, according to the context of the behavior that is currently running. Based on the human attention focus, the agent is also dotted of a affective state. The agent s affective state is based on theories of human emotion, mood and personality. This model serves as a basis for the mechanism of continuous adjustment of the agent s attention focus, both the qualitative and the quantative focus. With this mechanism, the agent can adjust its focus of attention during the execution of the behavior, in order to become more efficient in the face of environmental changes. The proposed architecture can be used in a very flexibly way. The focus of attention can work in a fixed way (neither the qualitative focus nor the quantitaive focus one changes), as well as using different combinations for the qualitative and quantitative foci variation. The architecture was built on a platform for BDI agents, but its design allows it to be used in any other type of agents, since the implementation is made only in the perception level layer of the agent. In order to evaluate the contribution proposed in this work, an extensive series of experiments were conducted on an agent-based simulation over a fire-growing scenario. In the simulations, the agents using the architecture proposed in this work are compared with similar agents (with the same reasoning model), but able to process all the information sent by the environment. Intuitively, it is expected that the omniscient agent would be more efficient, since they can handle all the possible option before taking a decision. However, the experiments showed that attention-focus based agents can be as efficient as the omniscient ones, with the advantage of being able to solve the same problems in a significantly reduced time. Thus, the experiments indicate the efficiency of the proposed architecture

The impact of coordination on the effectiveness of last mile relief distribution

Last mile relief distribution is the final stage of humanitarian logistics. It refers to the supply of relief items from local distribution centers to the disaster affected people (Balcik et al., 2008). In the last mile relief distribution literature, researchers have focused on the use of optimisation techniques for determining the exact optimal solution (Liberatore et al., 2014), but there is a need to include behavioural factors with those optimisation techniques in order to obtain better predictive results. This paper will explain how improving the coordination factor increases the effectiveness of the last mile relief distribution process. There are two stages of methodology used to achieve the goal: Interviews: The authors conducted interviews with the Indian Government and with South Asian NGOs to identify the critical factors for final relief distribution. After thematic and content analysis of the interviews and the reports, the authors found some behavioural factors which affect the final relief distribution. Model building: Last mile relief distribution in India follows a specific framework described in the Indian Government disaster management handbook. We modelled this framework using agent based simulation and investigated the impact of coordination on effectiveness. We define effectiveness as the speed and accuracy with which aid is delivered to affected people. We tested through simulation modelling whether coordination improves effectiveness.

Investigating the Tradespace between Increased Automation and Optimal Manning on Aircraft Carrier Decks

With increasing prevalence and capabilities of autonomous systems as part of complex heterogeneous manned-unmanned environments (HMUEs), an important consideration is the impact of the introduction of automation on the optimal assignment of human personnel. The US Navy has implemented optimal staffing techniques before in the 1990's and 2000's with a "minimal staffing" approach. The results were poor, leading to the degradation of Naval preparedness. Clearly, another approach to determining optimal staffing is necessary. To this end, the goal of this research is to develop human performance models for use in determining optimal manning of HMUEs. The human performance models are developed using an agent-based simulation of the aircraft carrier flight deck, a representative safety-critical HMUE. The Personnel Multi-Agent Safety and Control Simulation (PMASCS) simulates and analyzes the effects of introducing generalized maintenance crew skill sets and accelerated failure repair times on the overall performance and safety of the carrier flight deck. A behavioral model of four operator types (ordnance officers, chocks and chains, fueling officers, plane captains, and maintenance operators) is presented here along with an aircraft failure model. The main focus of this work is on the maintenance operators and aircraft failure modeling, since they have a direct impact on total launch time, a primary metric for carrier deck performance. With PMASCS I explore the effects of two variables on total launch time of 22 aircraft: 1) skill level of maintenance operators and 2) aircraft failure repair times while on the catapult (referred to as Phase 4 repair times). It is found that neither introducing a generic skill set to maintenance crews nor introducing a technology to accelerate Phase 4 aircraft repair times improves the average total launch time of 22 aircraft. An optimal manning level of 3 maintenance crews is found under all conditions, the point at which any additional maintenance crews does not reduce the total launch time. An additional discussion is included about how these results change if the operations are relieved of the bottleneck of installing the holdback bar at launch time.

Methods, Models & Systems for Dealing with Some Business, Management & Engineering Problems

This keynote presentation will report some of our research work and experience on the development and applications of relevant methods, models, systems and simulation techniques in support of different types and various levels of decision making for business, management and engineering. In particular, the following topics will be covered. Modelling, multi-agent-based simulation and analysis of the allocation management of carbon dioxide emission permits in China (Nanfeng Liu & Shuliang Li Agent-based simulation of the dynamic evolution of enterprise carbon assets (Yin Zeng & Shuliang Li) A framework & system for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps: a big data perspective (Jin Xu, Zheng Li, Shuliang Li & Yanyan Zhang) Open innovation: intelligent model, social media & complex adaptive system simulation (Shuliang Li & Jim Zheng Li) A framework, model and software prototype for modelling and simulation for deshopping behaviour and how companies respond (Shawkat Rahman & Shuliang Li) Integrating multiple agents, simulation, knowledge bases and fuzzy logic for international marketing decision making (Shuliang Li & Jim Zheng Li) A Web-based hybrid intelligent system for combined conventional, digital, mobile, social media and mobile marketing strategy formulation (Shuliang Li & Jim Zheng Li) A hybrid intelligent model for Web & social media dynamics, and evolutionary and adaptive branding (Shuliang Li) A hybrid paradigm for modelling, simulation and analysis of brand virality in social media (Shuliang Li & Jim Zheng Li) Network configuration management: attack paradigms and architectures for computer network survivability (Tero Karvinen & Shuliang Li)