The effect of load on agent-based algorithms for distributed task allocation

Multi-agent algorithms inspired by the division of labour in social insects and by markets, are applied to a constrained problem of distributed task allocation. The efficiency (average number of tasks performed), the flexibility (ability to react to changes in the environment), and the sensitivity to load (ability to cope with differing demands) are investigated in both static and dynamic environments. A hybrid algorithm combining both approaches, is shown to exhibit improved efficiency and robustness. We employ nature inspired particle swarm optimisation to obtain optimised parameters for all algorithms in a range of representative environments. Although results are obtained for large population sizes to avoid finite size effects, the influence of population size on the performance is also analysed. From a theoretical point of view, we analyse the causes of efficiency loss, derive theoretical upper bounds for the efficiency, and compare these with the experimental results

Development of a Transportation Network Model for Complex Economic and Infrastructure Simulations

The intent of this effort is to add a transport network to an agent-based economic simulation model, thereby increasing the fidelity of the economic results reported. The majority of existing agent-based work regarding transportation infrastructures deals with traffic management and urban planning. However, little work has been done in modeling the transport system as a basic infrastructure dependency for an agent-based representation of the economy. In an agent-based modeling environment the transportation component derives its demand from the activities of the agents as they buy and sell goods which require transportation services. The Network Shipper agent was added to allow transportation based on the existing U.S. interstate highway system. The agent determines the shortest path between a buyer and seller and estimates a time of arrival. To represent the dynamic nature of a highway system capacity and speed constraints are imposed on the network. The transportation network was then tested using data for the US milk supply chain. The strongest result of this work is the demonstration that inventory levels in a supply chain must buffer the delivery time uncertainty created when rigorous pursuit of minimum cost supply creates chum in the set of preferred suppliers for a firm. The current geographic distribution of supply and demand, along with variations in the effective time-dependent throughput capacity of the transportation network across the country, creates differential regional sensitivities. In particular, the North Atlantic region is most susceptible to this condition, and as a consequence experiences almost twice the price fluctuation of the South Atlantic region for cheese, despite having half the average supply distance of the south

CSP Dinámico: Un algoritmo dinámico para la resecuenciación en un almacén de líneas en paralelo

[EN] This paper shows the model used for resequencing where a selectivity bank consisting of parallel line segments is applied to reshuffle a given initial sequence and rule violations are to be minimized.[ES] En el presente trabajo se muestra el modelo utilizado para la resecuenciación en una línea de ensamblaje con mezcla de modelos donde un almacén con configuración en líneas en paralelo se utiliza para resecuenciar y minimizar la violación de restricciones de la línea de montaje.El presente trabajo se ha desarrollado gracias a la ayuda DPI2010-18243 del Ministerio de Ciencia e Innovación del Gobierno de España dentro del programa de Proyectos de Investigación Fundamental no orientada, con el título "Coordinación de operaciones en redes de suministro/demanda ajustadas, resilientes a la incertidumbre: modelos y algoritmos para la gestion de la incertidumbre y la complejidad". Este trabajo también ha sido financiado parcialmente a partir del proyecto DPI2011-27633 y título “Programacion de produccion en cadenas de suministro sincronizadas multietapa con ensamblajes/desensamblajes con renovacion constante de productos en un contexto de innovación”Valero-Herrero, M.; Molina Morte, P. (2013). CSP Dinámico: Un algoritmo dinámico para la resecuenciación en un almacén de líneas en paralelo. Working Papers on Operations Management. 4(1):23-33. https://doi.org/10.4995/wpom.v4i1.1234SWORD233341Inman, R. R., & Schmeling, D. M. (2003). Algorithm for agile assembling-to-order in the automotive industry. International Journal of Production Research, 41(16), 3831-3848. doi:10.1080/00207540310001595792Jayaraman, A., Narayanaswamy, R., & Gunal, A. K. (1997). A Sortation System Model, in Simulation Conference, 1997., Proceedings of the 1997 Winter, pp. 866-871.Kittithreerapronchai, O. & Anderson, C. (2003). Do ants paint trucks better than chickens? Markets versus response thresholds for distributed dynamic scheduling, in Evolutionary Computation, 2003. CEC '03. The 2003 Congress on, pp. 1431-1439.Valero-Herrero, M., Garcia-Sabater, J. P., & Maheut, J. (2011b). An approach to the real circumstances of the car sequencing problem, in 41st International Conference on Computers and Industrial Engineering

Culpable ignorance in a collective setting

This paper explores types of organisational ignorance and ways in which organisational practices can affect the knowledge we have about the causes and effects of our actions. I will argue that because knowledge and information are not evenly distributed within an organisation, sometimes organisational design alone can create individual ignorance. I will also show that sometimes the act that creates conditions for culpable ignorance takes place at the collective level. This suggests that quality of will of an agent is not necessary to explain culpable ignorance in an organisational setting.Peer reviewe

Constructing living buildings: a review of relevant technologies for a novel application of biohybrid robotics

Biohybrid robotics takes an engineering approach to the expansion and exploitation of biological behaviours for application to automated tasks. Here, we identify the construction of living buildings and infrastructure as a high-potential application domain for biohybrid robotics, and review technological advances relevant to its future development. Construction, civil infrastructure maintenance and building occupancy in the last decades have comprised a major portion of economic production, energy consumption and carbon emissions. Integrating biological organisms into automated construction tasks and permanent building components therefore has high potential for impact. Live materials can provide several advantages over standard synthetic construction materials, including self-repair of damage, increase rather than degradation of structural performance over time, resilience to corrosive environments, support of biodiversity, and mitigation of urban heat islands. Here, we review relevant technologies, which are currently disparate. They span robotics, self-organizing systems, artificial life, construction automation, structural engineering, architecture, bioengineering, biomaterials, and molecular and cellular biology. In these disciplines, developments relevant to biohybrid construction and living buildings are in the early stages, and typically are not exchanged between disciplines. We, therefore, consider this review useful to the future development of biohybrid engineering for this highly interdisciplinary application.publishe

Design of Complex Engineered Systems Using Multiagent Coordination

This thesis is the combination of two research publications working toward a unified strategy in which the design of complex engineered systems can be completed using a multiagent coordination approach. Current engineered system modeling techniques segment large complex models into multiple groups to be simulated independently. These methods restrict the evaluations of such complex systems, as their failure properties are typically unknown until they are experienced in operation. In an effort to help engineers to design complex engineered systems, this research proposes that a distributed yet non-legislated approach can be used in the design processes by splitting up the overall system into specific teams. The approach specifically hypothesizes that multiagent credit assignment can be used to effectively determine how to properly incentivize subsystem designers so that the global set of system-level objectives can be achieved. The first publication presents a multiagent systems based approach for designing a self-replicating robotic manufacturing factory in space. The simulation in this work is able to present the coordination of the agents during the construction of the factory as the parameters of the learning algorithm are changed. The results show the advantage of using a learning algorithm to design a large system. The second publication presents a hybrid approach to design complex engineered systems, providing a method in which design decisions can be reconciled without the need for either detailed interaction models or external legislating mechanisms. The results of this paper demonstrate that a team of autonomous agents using a cooperative coevolutionary algorithm can effectively design a complex engineered system. Each publication utilized a system model to illustrate and simulate the methods and potential results. By designing complex systems with a multiagent coordination approach, a design methodology can be developed in an effort to reduce design uncertainty and provide mechanisms through which the system level impact of decisions can be estimated without explicitly modeling such interactions

Bio-inspired multi-agent systems for reconfigurable manufacturing systems

The current market’s demand for customization and responsiveness is a major challenge for producing intelligent, adaptive manufacturing systems. The Multi-Agent System (MAS) paradigm offers an alternative way to design this kind of system based on decentralized control using distributed, autonomous agents, thus replacing the traditional centralized control approach. The MAS solutions provide modularity, flexibility and robustness, thus addressing the responsiveness property, but usually do not consider true adaptation and re-configuration. Understanding how, in nature, complex things are performed in a simple and effective way allows us to mimic nature’s insights and develop powerful adaptive systems that able to evolve, thus dealing with the current challenges imposed on manufactur- ing systems. The paper provides an overview of some of the principles found in nature and biology and analyses the effectiveness of bio-inspired methods, which are used to enhance multi-agent systems to solve complex engineering problems, especially in the manufacturing field. An industrial automation case study is used to illustrate a bio-inspired method based on potential fields to dynamically route pallets