MULTI AGENT-BASED ENVIRONMENTAL LANDSCAPE (MABEL) - AN ARTIFICIAL INTELLIGENCE SIMULATION MODEL: SOME EARLY ASSESSMENTS

The Multi Agent-Based Environmental Landscape model (MABEL) introduces a Distributed Artificial Intelligence (DAI) systemic methodology, to simulate land use and transformation changes over time and space. Computational agents represent abstract relations among geographic, environmental, human and socio-economic variables, with respect to land transformation pattern changes. A multi-agent environment is developed providing task-nonspecific problem-solving abilities, flexibility on achieving goals and representing existing relations observed in real-world scenarios, and goal-based efficiency. Intelligent MABEL agents acquire spatial expressions and perform specific tasks demonstrating autonomy, environmental interactions, communication and cooperation, reactivity and proactivity, reasoning and learning capabilities. Their decisions maximize both task-specific marginal utility for their actions and joint, weighted marginal utility for their time-stepping. Agent behavior is achieved by personalizing a dynamic utility-based knowledge base through sequential GIS filtering, probability-distributed weighting, joint probability Bayesian correlational weighting, and goal-based distributional properties, applied to socio-economic and behavioral criteria. First-order logics, heuristics and appropriation of time-step sequences employed, provide a simulation-able environment, capable of re-generating space-time evolution of the agents.Environmental Economics and Policy,

Organisational challenges for local maize value chains in the biobased economy

Societal challenges drive an increased interest to transform our fossil resources based to a biobased economy, in which biomass is used for the production of bioenergy and biomaterials. Research aiming to enhance this biobased economy often focuses on the technical and techno-economic aspects of converting biomass into value-added biobased products, but fails to take into account non-technical aspects, such as the organizational challenges related to local biomass value chains. These organizational challenges originate from the unique characteristics of the biomass itself, and those of the economic agents involved in the value chain. In this dissertation, we therefore focused on the organizational aspects of local biomass value chains for new applications within the biobased economy. We used local maize value chains in Flanders as case-study. Our research integrated findings from qualitative research with simulation results from a quantitative dynamic modelling approach, being agent-based modelling. We demonstrated the importance of the local context in the trade of silage maize, and identified several organizational challenges that need to be addressed for the development of a corn stover value chain in Flanders. This allows us to formulate five practical recommendations for practitioners: (1) try to work with intermediaries when you are a new entrant into an already existing local biomass value chain; (2) retain an adequate level of flexibility; (3) make a well-considered choice about the organizational form of new value chains; (4) make sure all stakeholders are involved when developing new local biomass value chains for new applications in the biobased economy; and (5) pay special attention to create trust and enthusiasm for the new value chain amongst all stakeholders involved. In general, we advocate a value chain perspective when developing new local biomass value chains for the biobased economy

Collaborative and adaptive supply chain planning

Dans le contexte industriel d'aujourd'hui, la compétitivité est fortement liée à la performance de la chaîne d'approvisionnement. En d'autres termes, il est essentiel que les unités d'affaires de la chaîne collaborent pour coordonner efficacement leurs activités de production, de façon a produire et livrer les produits à temps, à un coût raisonnable. Pour atteindre cet objectif, nous croyons qu'il est nécessaire que les entreprises adaptent leurs stratégies de planification, que nous appelons comportements, aux différentes situations auxquelles elles font face. En ayant une connaissance de l'impact de leurs comportements de planification sur la performance de la chaîne d'approvisionnement, les entreprises peuvent alors adapter leur comportement plutôt que d'utiliser toujours le même. Cette thèse de doctorat porte sur l'adaptation des comportements de planification des membres d'une même chaîne d'approvisionnement. Chaque membre pouvant choisir un comportement différent et toutes les combinaisons de ces comportements ayant potentiellement un impact sur la performance globale, il est difficile de connaître à l'avance l'ensemble des comportements à adopter pour améliorer cette performance. Il devient alors intéressant de simuler les différentes combinaisons de comportements dans différentes situations et d'évaluer les performances de chacun. Pour permettre l'utilisation de plusieurs comportements dans différentes situations, en utilisant la technologie à base d'agents, nous avons conçu un modèle d'agent à comportements multiples qui a la capacité d'adapter son comportement de planification selon la situation. Les agents planificateurs ont alors la possibilité de se coordonner de façon collaborative pour améliorer leur performance collective. En modélisant les unités d'affaires par des agents, nous avons simulé avec la plateforme de planification à base d'agents de FORAC des agents utilisant différents comportements de planification dits de réaction et de négociation. Cette plateforme, développée par le consortium de recherche FORAC de l'Université Laval, permet de simuler des décisions de planification et de planifier les opérations de la chaîne d'approvisionnement. Ces comportements de planification sont des métaheurisciques organisationnelles qui permettent aux agents de générer des plans de production différents. La simulation est basée sur un cas illustrant la chaîne d'approvisionnement de l'industrie du bois d'œuvre. Les résultats obtenus par l'utilisation de multiples comportements de réaction et de négociation montrent que les systèmes de planification avancée peuvent tirer avantage de disposer de plusieurs comportements de planification, en raIson du contexte dynamique des chaînes d'approvisionnement. La pertinence des résultats de cette thèse dépend de la prémisse que les entreprises qui adapteront leurs comportements de planification aux autres et à leur environnement auront un avantage concurrentiel important sur leurs adversaires

Data and Design: Advancing Theory for Complex Adaptive Systems

Complex adaptive systems exhibit certain types of behaviour that are difficult to predict or understand using reductionist approaches, such as linearization or assuming conditions of optimality. This research focuses on the complex adaptive systems associated with public health. These are noted for being driven by many latent forces, shaped centrally by human behaviour. Dynamic simulation techniques, including agent-based models (ABMs) and system dynamics (SD) models, have been used to study the behaviour of complex adaptive systems, including in public health. While much has been learned, such work is still hampered by important limitations. Models of complex systems themselves can be quite complex, increasing the difficulty in explaining unexpected model behaviour, whether that behaviour comes from model code errors or is due to new learning. Model complexity also leads to model designs that are hard to adapt to growing knowledge about the subject area, further reducing model-generated insights. In the current literature of dynamic simulations of human public health behaviour, few focus on capturing explicit psychological theories of human behaviour. Given that human behaviour, especially health and risk behaviour, is so central to understanding of processes in public health, this work explores several methods to improve the utility and flexibility of dynamic models in public health. This work is undertaken in three projects. The first uses a machine learning algorithm, the particle filter, to augment a simple ABM in the presence of continuous disease prevalence data from the modelled system. It is shown that, while using the particle filter improves the accuracy of the ABM, when compared with previous work using SD with a particle filter, the ABM has some limitations, which are discussed. The second presents a model design pattern that focuses on scalability and modularity to improve the development time, testability, and flexibility of a dynamic simulation for tobacco smoking. This method also supports a general pattern of constructing hybrid models --- those that contain elements of multiple methods, such as agent-based or system dynamics. This method is demonstrated with a stylized example of tobacco smoking in a human population. The final line of work implements this modular design pattern, with differing mechanisms of addiction dynamics, within a rich behavioural model of tobacco purchasing and consumption. It integrates the results from a discrete choice experiment, which is a widely used economic method for study human preferences. It compares and contrasts four independent addiction modules under different population assumptions. A number of important insights are discussed: no single module was universally more accurate across all human subpopulations, demonstrating the benefit of exploring a diversity of approaches; increasing the number of parameters does not necessarily improve a module's predictions, since the overall least accurate module had the second highest number of parameters; and slight changes in module structure can lead to drastic improvements, implying the need to be able to iteratively learn from model behaviour

A First Approach on Modelling Staff Proactiveness in Retail Simulation Models

There has been a noticeable shift in the relative composition of the industry in the developed countries in recent years; manufacturing is decreasing while the service sector is becoming more important. However, currently most simulation models for investigating service systems are still built in the same way as manufacturing simulation models, using a process-oriented world view, i.e. they model the flow of passive entities through a system. These kinds of models allow studying aspects of operational management but are not well suited for studying the dynamics that appear in service systems due to human behaviour. For these kinds of studies we require tools that allow modelling the system and entities using an object-oriented world view, where intelligent objects serve as abstract \'actors\' that are goal directed and can behave proactively. In our work we combine process-oriented discrete event simulation modelling and object-oriented agent based simulation modelling to investigate the impact of people management practices on retail productivity. In this paper, we reveal in a series of experiments what impact considering proactivity can have on the output accuracy of simulation models of human centric systems. The model and data we use for this investigation are based on a case study in a UK department store. We show that considering proactivity positively influences the validity of these kinds of models and therefore allows analysts to make better recommendations regarding strategies to apply people management practices.Retail Performance, Management Practices, Proactive Behaviour, Service Experience, Agent-Based Modelling, Simulation

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

From Network to Web dimension in supply chain management

Cette thèse soutient que la dimension réseau, étant actuellement la portée du domaine de la gestion de chaîne logistique, contraint l’avancement de ce domaine et restreint des innovations conceptuelles et fondamentales capables d’adresser les grands défis économiques, environnementaux et sociaux. Les concepts de chaîne et de réseau ne reflètent pas la complexité des flux physiques, informationnels et financiers générés par les interactions qui ont lieu dans des réseaux interconnectés. Ces concepts n’offrent pas les fondations théoriques pour supporter des interventions allant au-delà d’un seul réseau et laissent échapper des opportunités nécessitant une vision multi-réseau. Ainsi, la dimension “web”, celle des réseaux de réseaux, est proposée comme une extension de la dimension réseau. Cette extension peut être vue comme l’étape naturelle suivante dans la progression qui a commencé par le niveau de gestion des opérations internes, est passée au niveau de la chaîne logistique et se trouve actuellement au niveau du réseau logistique. Après l’investigation théorique des raisons et de la façon d’intégrer la dimension web dans le domaine de la gestion de la chaîne logistique, la thèse étudie des implications importantes de cette intégration sur la collaboration inter-organisationnelle et le processus de prise de décision dans des environnements de webs logistiques. Elle démontre, en exploitant l’exemple des réseaux interconnectés ouverts, des potentialités inimaginables sans une vision web. Une méthodologie de conception d’un modèle de simulation permettant l’évaluation et la comparaison des webs ouverts par rapport aux webs existants est proposée. Puisque l’aide à la décision est une composante importante de la gestion de la chaîne logistique, la thèse contribue à déterminer les besoins des gestionnaires et à identifier les lignes directrices de la conception des outils d’aide à la décision offrant le support adéquat pour faire face aux défis et à la complexité des webs logistiques. Ces lignes directrices ont été compilées dans un cadre de conception des logiciels d’aide à la décision supportant la dimension web. Ce cadre est exploité pour développer quatre applications logicielles offrant aux praticiens et aux chercheurs des outils nécessaires pour étudier, analyser et démêler la complexité des webs logistiques.This thesis argues that the network dimension as the current scope of supply chain management is confining the evolution of this field and restricting the conceptual and fundamental innovations required for addressing the major challenges imposed by the evolution of markets and the increased intricacies of business relationships. The concepts of chain and network are limitative when attempting to represent the complexity of physical, informational and financial flows resulting from the interactions occurring in overlapping networks. They lack the theoretical foundations necessary to explain and encompass initiatives that go beyond a single chain or network. They also lead to overlook substantial opportunities that require beyond a network vision. Therefore, the “web” dimension, as networks of networks, is proposed as an extension to the network dimension in supply chain management. This new scope is the natural next step in the progression from the internal operations management level to the supply chain level and then to the supply network level. After a theoretical investigation of why and how the web dimension should be integrated into the supply chain management field, the thesis studies and discusses important implications of this integration on inter-organisational collaboration and of the decision-making processes in the logistic web environments. It demonstrates through the example of open interconnected logistic webs some of the potentials that cannot be imagined without a web vision. A methodology for designing a simulation model to assess the impact of such open webs versus existing webs is proposed. Since decision support is a key element in supply chain management, the thesis contributes to determine the needs of supply chain managers and identify the important axes for designing decision support systems that provide adequate assistance in dealing with the challenges and complexity presented by logistic web environments. The identified elements result in the establishment of a foundation for designing software solutions required to handle the challenges revealed by the web dimension. This conceptual framework is applied to the prototyping of four applications that have the potential of providing practitioners and researchers with the appropriate understanding and necessary tools to deal with the complexity of logistics webs