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Smart Growth (SG) is an approach for sustainable urban development, it emerged to restrain the drawbacks of Metropolitan Areas’ urban sprawl. This approach enhances social equity and environmental justice through policies covering micro and macro levels, in addition, it discusses sustainability aspects. However, there are few attempts that simulate the effect of applying principles of SG on emergent behaviour within different context. This study aims at initiating a platform for building a SG Agent Based Model SGABM which focuses on the social behaviour, in order to assist in management of growth dynamics and build an information database for Urban Facility Management. The paper reviews literature and undergoes an application on Walkability principle.

The article investigates a generic framework to estimate maintenance costs attributed to the No Fault Found (NFF) phenomenon. Such overhead costs are particularly difficult to quantify due to potentially serviceable equipment being returned for repair. Other factors, such as a reduction in the availability of the system, compromising reliability of high value assets, and logistical factors, can all contribute to the cost of resolving an unknown fault. Here we apply the soft systems methodology to capture the critical cost drivers of NFF across the supply chain and build a framework to estimate the cost of NFF. We use a multi-method design including an online survey, workshops and semi-structured interviews to study NFF related cost practices based on information from 12 key participants across 7 UK organisations. The study identifies the major NFF cost drivers across the supply chain (e.g. transportation), the OEM (e.g. inventory) and the customer (e.g. lost man hours). An agent based model is used to evaluate the impact of these cost drivers on the overall NFF cost. The analysis shows how the most appropriate drivers can be selected to represent the cumulative costs due to NFF events and their impacts across the supply network. From the academic perspective, the generic framework for NFF cost estimation demonstrates how qualitative and quantitative information can be used together to achieve maintenance objectives. From a practical perspective, by applying the framework on one component, an organisation has the liberty to analyse the cost of NFF for that particular unit only.

Objective Design task assignment algorithms based on the patterns of disease spread among the population. Scope Epidemiology studies spatiotemporal patterns of illness in populations and the factors affecting it. An epidemic emerges out of the population activities and environment. Task assignment is a common activity in many realms where sub-tasks are created, delegated, and collectively carried out to achieve the original task. Due to its complexity and context, task assignment can be a challenging activity that can result in limited outcomes. This research studies task assignment as an epidemic assigned to a distributed system. We have developed computational models to understand the outbreak of aerosol-borne diseases by using the agent-based modelling approach. Experiments are carried out to observe the patterns of emergence during the spread of disease among the individuals and get insights of their mechanisms. These mechanisms are used to design algorithms for task assignment on distributed systems. Results Understanding the emergent behaviour of diseases can provide the platform for the development of distributed algorithms that can be helpful in overcoming some of the challenges of task assignment in a distributed system.

Systems intelligence is the ability to act intelligently within complex systems involving interaction and feedback. Organizations and social groups are typical examples of everyday systems. The dynamics of social systems can be difficult to understand because of their systemic nature. This makes positively affecting the state of the system a challenging problem. The effects of positive emotions have been linked with increased performance in social groups and individuals. Thus simulating emotion dynamics can be used to better understand how to act more constructively within organizations. PoSITeams is a web-based multi-agent simulator to study the dynamics of emotions. We present a novel agent-based emotional contagion model based on psychological research to study the dynamics of positive and negative emotions in organizations. The purpose of the simulator is to let the user explore the effects of different behavioural and structural changes in organizations. This facilitates perceiving the organization as a system and also lets the user recognize the potential of changing the system from within, thus promoting systems intelligent behaviour in the organization. The presented emotional contagion model is also considered as an optimization problem to let the simulator suggest systems intelligent actions. The behaviour of the model and the optimization methods are examined with example simulations.