Organizational change, quality and cybernetics

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Tracking of non-stationary time-series using resource allocating RBF networks

In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Using electricity load data and training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise and forgetting factors for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. We also find that a recently-proposed alternative novelty criterion, found to be more robust in stationary environments, does not fare so well in the non-stationary case due to the need for filter adaptability during training.

Building a holarchy using business process-oriented holonic (PrOH) modeling

The application of systems thinking to designing, managing, and improving business processes has developed a new "holonic-based" process modeling methodology. The theoretical background and the methodology are described using examples taken from a large organization designing and manufacturing capital goods equipment operating within a complex and dynamic environment. A key point of differentiation attributed to this methodology is that it allows a set of models to be produced without taking a task breakdown approach but instead uses systems thinking and a construct known as the "holon" to build process descriptions as a system of systems (i.e., a holarchy). The process-oriented holonic modeling methodology has been used for total quality management and business process engineering exercises in different industrial sectors and builds models that connect the strategic vision of a company to its operational processes. Exercises have been conducted in response to environmental pressures to make operations align with strategic thinking as well as becoming increasingly agile and efficient. This unique methodology is best applied in environments of high complexity, low volume, and high variety, where repeated learning opportunities are few and far between (e.g., large development projects). © 2007 IEEE.

Combining analytic hierarchy process and goal programming for logistics distribution network design

Logistics distribution network design is one of the major decision problems arising in contemporary supply chain management. The decision involves many quantitative and qualitative factors that may be conflicting in nature. This paper applies an integrated multiple criteria decision making approach to design an optimal distribution network. In the approach, the analytic hierarchy process (AHP) is used first to determine the relative importance weightings or priorities of alternative warehouses with respect to both deliverer oriented and customer oriented criteria. Then, the goal programming (GP) model incorporating the constraints of system, resource, and AHP priority is formulated to select the best set of warehouses without exceeding the limited available resources. In this paper, two commercial packages are used: Expert Choice for determining the AHP priorities of the warehouses, and LINDO for solving the GP model. © 2007 IEEE.

A systems methodology for analysing and simulating manufacturing systems

The Systems Engineering Group (SEG) at De Montfort University are developing the Boardman Soft Systems Methodology (BSSM) which allows complex human systems to be modelled, this work builds upon Checkland's Soft Systems Methodology (1981). The BSSM has been applied to the modelling of the systems engineering process as used in design and manufacturing companies. The BSSM is used to solicit information from a company and this data is then transformed into systemic diagrams (systemigrams). These systemigrams are posited to be accurate and concise representations of the system which has been modelled. This paper describes the collaboration between SEG and a manufacturing company (MC) in Leicester, England. The purpose of this collaboration was twofold. First, it was to create an objective view of the MC's processes, in the form of systemigrams. It was important to get this modelled by a source outside of the company, as it is difficult for people within a system being modelled to be unbiased. Secondly, it allowed a series of systemigrams to be produced which can then be subjected to simulation, for the purpose of aiding risk management decisions and to reduce the project cycle time

Strategic information systems at the Colombian President's Office (1990-1992) : a managerial cybernetic approach

This research studies the issue of using strategic information technology for improving organisational effectiveness. It analyses different academic approaches explaining the nature of information systems and the need organisations feel of developing strategic information systems planning processes, to improve organisational effectiveness. It chooses Managerial Cybernetics as the theoretical foundation supporting development of a "Strategic Information Systems Planning" Framework, and uses it for supporting the analysis of a documented story about the process lived by the Colombian President's Office, in 1990-1992. It argues that by analysing the situation through this new analysis framework we may enlighten some previously unclear situations lived, and not yet properly explained through other approaches to strategic information systems planning. The documented history explains the organisational context and strategic postures of the Colombian President's Office and the Colombian Public Sector, at that time, as well as some of the strategic information systems defined and developed. In particular it analyses a system developed jointly by the President's Office and the National Planning Department, for measuring results of the main national development programmes. Then, it reviews these situations, in the light of the new framework and presents the main findings of the exercise. Finally, it analyses the whole research exercise, the perceived usefulness of the chosen frameworks and tools to enlighten the real situations analysed that were not clear enough, and some open research paths to follow for future researchers interested in the issue.

A cybernetic methodology to study and design human activities

This thesis offers a methodology to study and design effective communication mechanisms in human activities. The methodology is focused in the management of complexity. It is argued that complexity is not something objective that can be worked out analytically, but something subjective that depends on the viewpoint. Also it is argued that while certain social contexts may inhibit, others may enhance the viewpoint's capabilities to deal with complexity. Certain organisation structures are more likely than others to allow individuals to release their potentials. Thus, the relevance of studying and designing effective organisations. The first part of the thesis offers a `cybernetic methodology' for problem solving in human activities, the second offers a `method' to study and design organisations. The cybernetics methodology discussed in this work is rooted in second order cybernetics, or the cybernetics of the observing systems (Von Foester 1979, Maturana and Varela 1980). Its main tenet is that the known properties of the real world reside in the individual and not in the world itself. This view, which puts emphasis in a, by nature, one sided and unilateral appreciation of reality, triggers the need for dialogue and conversations to construct it. The `method' to study and design organisations, it based on Beer's Viable System Model (Beer 1979, 1981, 1985). This model permits us to assess how successful is an organisation in coping with its environmental complexity, and, moreover, permits us to establish how to make more effective the responses to this complexity. These features of the model are of great significance in a world where complexity is perceived to be growing at an unthinkable pace. But, `seeing' these features of the model assumes an effective appreciation of organisational complexity; hence the need for the methodological discussions offered by the first part of the thesis.

The evolution and design of safety management systems

Research in safety management has been inhibited by lack of consensus as to the definitions of the terms with which it is concerned and, in general, the lack of an agreed theoretical framework within which to collate and contrast empirical findings. This thesis sets out definitions of key terms (hazard, risk, accident, incident and safety) and provides a theoretical framework. This framework has been informed by many sources but especially the Management Oversight and Risk Tree (MORT), cybernetics and the Viable System Model (VSM). Fieldwork designs are proposed for the empirical development of an analytical framework and its use to assist study of the development of safety management in organisations.

The emergence of knowledge exchange:an agent-based model of a software market

We investigate knowledge exchange among commercial organizations, the rationale behind it, and its effects on the market. Knowledge exchange is known to be beneficial for industry, but in order to explain it, authors have used high-level concepts like network effects, reputation, and trust. We attempt to formalize a plausible and elegant explanation of how and why companies adopt information exchange and why it benefits the market as a whole when this happens. This explanation is based on a multiagent model that simulates a market of software providers. Even though the model does not include any high-level concepts, information exchange naturally emerges during simulations as a successful profitable behavior. The conclusions reached by this agent-based analysis are twofold: 1) a straightforward set of assumptions is enough to give rise to exchange in a software market, and 2) knowledge exchange is shown to increase the efficiency of the market.

Community relation discovery by named entities

Discovering who works with whom, on which projects and with which customers is a key task in knowledge management. Although most organizations keep models of organizational structures, these models do not necessarily accurately reflect the reality on the ground. In this paper we present a text mining method called CORDER which first recognizes named entities (NEs) of various types from Web pages, and then discovers relations from a target NE to other NEs which co-occur with it. We evaluated the method on our departmental Website. We used the CORDER method to first find related NEs of four types (organizations, people, projects, and research areas) from Web pages on the Website and then rank them according to their co-occurrence with each of the people in our department. 20 representative people were selected and each of them was presented with ranked lists of each type of NE. Each person specified whether these NEs were related to him/her and changed or confirmed their rankings. Our results indicate that the method can find the NEs with which these people are closely related and provide accurate rankings.

Stability of multi-agent systems

This work attempts to shed light to the fundamental concepts behind the stability of Multi-Agent Systems. We view the system as a discrete time Markov chain with a potentially unknown transitional probability distribution. The system will be considered to be stable when its state has converged to an equilibrium distribution. Faced with the non-trivial task of establishing the convergence to such a distribution, we propose a hypothesis testing approach according to which we test whether the convergence of a particular system metric has occurred. We describe some artificial multi-agent ecosystems that were developed and we present results based on these systems which confirm that this approach qualitatively agrees with our intuition.

Using the max-sum algorithm for supply chain emergence in dynamic multiunit environments

Supply chain formation (SCF) is the process of determining the set of participants and exchange relationships within a network with the goal of setting up a supply chain that meets some predefined social objective. Many proposed solutions for the SCF problem rely on centralized computation, which presents a single point of failure and can also lead to problems with scalability. Decentralized techniques that aid supply chain emergence offer a more robust and scalable approach by allowing participants to deliberate between themselves about the structure of the optimal supply chain. Current decentralized supply chain emergence mechanisms are only able to deal with simplistic scenarios in which goods are produced and traded in single units only and without taking into account production capacities or input-output ratios other than 1:1. In this paper, we demonstrate the performance of a graphical inference technique, max-sum loopy belief propagation (LBP), in a complex multiunit unit supply chain emergence scenario which models additional constraints such as production capacities and input-to-output ratios. We also provide results demonstrating the performance of LBP in dynamic environments, where the properties and composition of participants are altered as the algorithm is running. Our results suggest that max-sum LBP produces consistently strong solutions on a variety of network structures in a multiunit problem scenario, and that performance tends not to be affected by on-the-fly changes to the properties or composition of participants.

The 'law of requisite variety' may assist climate change negotiations:a review of the Kyoto and Durban meetings

Ashby wrote about cybernetics, during which discourse he described a Law that attempts to resolve difficulties arising in complex situations – he suggested using variety to combat complexity. In this paper, we note that the delegates to the UN Framework Convention on Climate Change (UNFCCC) meeting in Kyoto, 1997, were offered a ‘simplifying solution’ to cope with the complexity of discussing multiple pollutants allegedly contributing to ‘climate change’. We assert that the adoption of CO2eq has resulted in imprecise thinking regarding the ‘carbon footprint’ – that is, ‘CO2’ – to the exclusion of other pollutants. We propose, as Ashby might have done, that the CO2eq and other factors within the ‘climate change’ negotiations be disaggregated to allow careful and specific individual solutions to be agreed on each factor. We propose a new permanent and transparent ‘action group’ be in charge of agenda setting and to manage the messy annual meetings. This body would be responsible for achieving accords at these annual meetings, rather than forcing this task on national hosts. We acknowledge the task is daunting and we recommend moving on from Ashby's Law to Beer's Viable Systems approach.

Scalable harmonization of complex networks with local controllers

Computational and communication complexities call for distributed, robust, and adaptive control. This paper proposes a promising way of bottom-up design of distributed control in which simple controllers are responsible for individual nodes. The overall behavior of the network can be achieved by interconnecting such controlled loops in cascade control for example and by enabling the individual nodes to share information about data with their neighbors without aiming at unattainable global solution. The problem is addressed by employing a fully probabilistic design, which can cope with inherent uncertainties, that can be implemented adaptively and which provide a systematic rich way to information sharing. This paper elaborates the overall solution, applies it to linear-Gaussian case, and provides simulation results.

Biologically inspired features for scene classification in video surveillance

Inspired by human visual cognition mechanism, this paper first presents a scene classification method based on an improved standard model feature. Compared with state-of-the-art efforts in scene classification, the newly proposed method is more robust, more selective, and of lower complexity. These advantages are demonstrated by two sets of experiments on both our own database and standard public ones. Furthermore, occlusion and disorder problems in scene classification in video surveillance are also first studied in this paper. © 2010 IEEE.