Developing a decision framework for the strategic sourcing of biomass

The deployment of bioenergy technologies is a key part of UK and European renewable energy policy. A key barrier to the deployment of bioenergy technologies is the management of biomass supply chains including the evaluation of suppliers and the contracting of biomass. In the undeveloped biomass for energy market buyers of biomass are faced with three major challenges during the development of new bioenergy projects. What characteristics will a certain supply of biomass have, how to evaluate biomass suppliers and which suppliers to contract with in order to provide a portfolio of suppliers that best satisfies the needs of the project and its stakeholder group whilst also satisfying crisp and non-crisp technological constraints. The problem description is taken from the situation faced by the industrial partner in this research, Express Energy Ltd. This research tackles these three areas separately then combines them to form a decision framework to assist biomass buyers with the strategic sourcing of biomass. The BioSS framework. The BioSS framework consists of three modes which mirror the development stages of bioenergy projects. BioSS.2 mode for early stage development, BioSS.3 mode for financial close stage and BioSS.Op for the operational phase of the project. BioSS is formed of a fuels library, a supplier evaluation module and an order allocation module, a Monte-Carlo analysis module is also included to evaluate the accuracy of the recommended portfolios. In each mode BioSS can recommend which suppliers should be contracted with and how much material should be purchased from each. The recommended blend should have chemical characteristics within the technological constraints of the conversion technology and also best satisfy the stakeholder group. The fuels library is made up from a wide variety of sources and contains around 100 unique descriptions of potential biomass sources that a developer may encounter. The library takes a wide data collection approach and has the aim of allowing for estimates to be made of biomass characteristics without expensive and time consuming testing. The supplier evaluation part of BioSS uses a QFD-AHP method to give importance weightings to 27 different evaluating criteria. The evaluating criteria have been compiled from interviews with stakeholders and policy and position documents and the weightings have been assigned using a mixture of workshops and expert interview. The weighted importance scores allow potential suppliers to better tailor their business offering and provides a robust framework for decision makers to better understand the requirements of the bioenergy project stakeholder groups. The order allocation part of BioSS uses a chance-constrained programming approach to assign orders of material between potential suppliers based on the chemical characteristics of those suppliers and the preference score of those suppliers. The optimisation program finds the portfolio of orders to allocate to suppliers to give the highest performance portfolio in the eyes of the stakeholder group whilst also complying with technological constraints. The technological constraints can be breached if the decision maker requires by setting the constraint as a chance-constraint. This allows a wider range of biomass sources to be procured and allows a greater overall performance to be realised than considering crisp constraints or using deterministic programming approaches. BioSS is demonstrated against two scenarios faced by UK bioenergy developers. The first is a large scale combustion power project, the second a small scale gasification project. The Bioss is applied in each mode for both scenarios and is shown to adapt the solution to the stakeholder group importance and the different constraints of the different conversion technologies whilst finding a globally optimal portfolio for stakeholder satisfaction.

Analysis of the procedures associated with the decision to sub-contract work

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Quantitative analysis of multi-spectral fundus images

We have developed a new technique for extracting histological parameters from multi-spectral images of the ocular fundus. The new method uses a Monte Carlo simulation of the reflectance of the fundus to model how the spectral reflectance of the tissue varies with differing tissue histology. The model is parameterised by the concentrations of the five main absorbers found in the fundus: retinal haemoglobins, choroidal haemoglobins, choroidal melanin, RPE melanin and macular pigment. These parameters are shown to give rise to distinct variations in the tissue colouration. We use the results of the Monte Carlo simulations to construct an inverse model which maps tissue colouration onto the model parameters. This allows the concentration and distribution of the five main absorbers to be determined from suitable multi-spectral images. We propose the use of "image quotients" to allow this information to be extracted from uncalibrated image data. The filters used to acquire the images are selected to ensure a one-to-one mapping between model parameters and image quotients. To recover five model parameters uniquely, images must be acquired in six distinct spectral bands. Theoretical investigations suggest that retinal haemoglobins and macular pigment can be recovered with RMS errors of less than 10%. We present parametric maps showing the variation of these parameters across the posterior pole of the fundus. The results are in agreement with known tissue histology for normal healthy subjects. We also present an early result which suggests that, with further development, the technique could be used to successfully detect retinal haemorrhages.

Decision theory to support evacuation in advance of catastrophic disaster including modular influence diagrams and spatial data analysis.

DUE TO INCOMPLETE PAPERWORK, ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

An efficient knowledge transfer solution to a novel SMDP formalization of a broker's decision problem

This paper introduces a new technique for optimizing the trading strategy of brokers that autonomously trade in re- tail and wholesale markets. Simultaneous optimization of re- tail and wholesale strategies has been considered by existing studies as intractable. Therefore, each of these strategies is optimized separately and their interdependence is generally ignored, with resulting broker agents not aiming for a glob- ally optimal retail and wholesale strategy. In this paper, we propose a novel formalization, based on a semi-Markov deci- sion process (SMDP), which globally and simultaneously op- timizes retail and wholesale strategies. The SMDP is solved using hierarchical reinforcement learning (HRL) in multi- agent environments. To address the curse of dimensionality, which arises when applying SMDP and HRL to complex de- cision problems, we propose an ecient knowledge transfer approach. This enables the reuse of learned trading skills in order to speed up the learning in new markets, at the same time as making the broker transportable across market envi- ronments. The proposed SMDP-broker has been thoroughly evaluated in two well-established multi-agent simulation en- vironments within the Trading Agent Competition (TAC) community. Analysis of controlled experiments shows that this broker can outperform the top TAC-brokers. More- over, our broker is able to perform well in a wide range of environments by re-using knowledge acquired in previously experienced settings.

A Multi-agent Framework for Distributed Decision-making Systems

An approach of building distributed decision support systems is proposed. There is defined a framework of a distributed DSS and examined questions of problem formulation and solving using artificial intellectual agents in system core.

Application of the Artificial Intelligence Algorithms for System Analysis of Multi Dimension Physiological Data for Developing Polyparametric Information System of Public Health Diagnostics

The polyparametric intelligence information system for diagnostics human functional state in medicine and public health is developed. The essence of the system consists in polyparametric describing of human functional state with the unified set of physiological parameters and using the polyparametric cognitive model developed as the tool for a system analysis of multitude data and diagnostics of a human functional state. The model is developed on the basis of general principles geometry and symmetry by algorithms of artificial intelligence systems. The architecture of the system is represented. The model allows analyzing traditional signs - absolute values of electrophysiological parameters and new signs generated by the model – relationships of ones. The classification of physiological multidimensional data is made with a transformer of the model. The results are presented to a physician in a form of visual graph – a pattern individual functional state. This graph allows performing clinical syndrome analysis. A level of human functional state is defined in the case of the developed standard (“ideal”) functional state. The complete formalization of results makes it possible to accumulate physiological data and to analyze them by mathematics methods.

Methods of Adaptive Extraction and Analysis of Knowledge for Knowledge-base Construction and Fast Decision Making

An approach for knowledge extraction from the information arriving to the knowledge base input and also new knowledge distribution over knowledge subsets already present in the knowledge base is developed. It is also necessary to realize the knowledge transform into parameters (data) of the model for the following decision-making on the given subset. It is assumed to realize the decision-making with the fuzzy sets’ apparatus.

Cramer-Rao bound analysis of location estimation in multi-hop wireless sensor networks

Location estimation is important for wireless sensor network (WSN) applications. In this paper we propose a Cramer-Rao Bound (CRB) based analytical approach for two centralized multi-hop localization algorithms to get insights into the error performance and its sensitivity to the distance measurement error, anchor node density and placement. The location estimation performance is compared with four distributed multi-hop localization algorithms by simulation to evaluate the efficiency of the proposed analytical approach. The numerical results demonstrate the complex tradeoff between the centralized and distributed localization algorithms on accuracy, complexity and communication overhead. Based on this analysis, an efficient and scalable performance evaluation tool can be designed for localization algorithms in large scale WSNs, where simulation-based evaluation approaches are impractical. © 2013 IEEE.

Using the framework method for the analysis of qualitative data in multi-disciplinary health research

Background: The Framework Method is becoming an increasingly popular approach to the management and analysis of qualitative data in health research. However, there is confusion about its potential application and limitations. Discussion. The article discusses when it is appropriate to adopt the Framework Method and explains the procedure for using it in multi-disciplinary health research teams, or those that involve clinicians, patients and lay people. The stages of the method are illustrated using examples from a published study. Summary. Used effectively, with the leadership of an experienced qualitative researcher, the Framework Method is a systematic and flexible approach to analysing qualitative data and is appropriate for use in research teams even where not all members have previous experience of conducting qualitative research. © 2013 Gale et al.; licensee BioMed Central Ltd.

Patients' and physicians' experiences of atrial fibrillation consultations and anticoagulation decision-making:a multi-perspective IPA design

OBJECTIVE: To explore patients' and physicians' experiences of atrial fibrillation consultations and oral anticoagulation decision-making. DESIGN: Multi-perspective interpretative phenomenological analyses. METHODS: Participants included small homogeneous subgroups: AF patients who accepted (n=4), refused (n=4), or discontinued (n=3) warfarin, and four physician subgroups (n=4 each group): consultant cardiologists, consultant general physicians, general practitioners and cardiology registrars. Semi-structured interviews were conducted. Transcripts were analysed using multi-perspective IPA analyses to attend to individuals within subgroups and making comparisons within and between groups. RESULTS: Three themes represented patients' experiences: Positioning within the physician-patient dyad, Health-life balance, and Drug myths and fear of stroke. Physicians' accounts generated three themes: Mechanised metaphors and probabilities, Navigating toward the 'right' decision, and Negotiating systemic factors. CONCLUSIONS: This multi-perspective IPA design facilitated an understanding of the diagnostic consultation and treatment decision-making which foregrounded patients' and physicians' experiences. We drew on Habermas' theory of communicative action to recommend broadening the content within consultations and shifting the focus to patients' life contexts. Interventions including specialist multidisciplinary teams, flexible management in primary care, and multifaceted interventions for information provision may enable the creation of an environment that supports genuine patient involvement and participatory decision-making.

Advanced predictive-analysis-based decision support for collaborative logistics networks

Purpose – The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution. Design/methodology/approach – The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments. Findings – Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes. Practical implications – The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept. Originality/value – The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.

Elemzés vagy megérzés: a stratégiai döntéshozatal gyakorlata Californiában és Magyarországon = Analysis or Intuition: Strategic decision making in California and Hungary

Stratégiai döntéseket jellemzően a vállalatok felsővezetői, vezérigazgatók és elnökök hoznak. Ennek szellemében 40 felsővezetőt kérdeztünk két nagyon különböző régióban (Kaliforniában és Magyarországon) egy összehasonlító kutatás keretében. A két országban tizenkét válaszadó vezérigazgató, elnök, alelnök, vagy felelős vezető volt (rájuk, mint Vezetőkre hivatkoztunk), miközben nyolcan alapítói és többségi tulajdonosai voltak saját vállalkozásuknak (őket nevezzük Vállalkozóknak). A kutatás három területre irányult: 1) Hogyan hoznak döntéseket a felsővezetők a valóságban a világ e két különböző táján; 2) Mennyiben különböznek - ha egyáltalán különböznek - a Vállalkozók és a Vezetők az alkalmazott döntéshozatali közelítésmódot tekintve, amikor az analitikus gondolkodást az intuícióikkal kombinálják; 3) Mik a hasonlóságok és a különbségek a menedzsment képességekben és a döntéshozatali rutinokban a Vállalkozók és a Vezetők között a vizsgált menedzsment kultúrákban. = Strategic decision making is usually conducted by a firm’s top management, led by the CEO or the President of the company. In keeping with this, 40 top level managers in two very different regions (California, USA and Hungary) were targeted in a comparative research study. In the two countries, twelve of the managers were CEOs, Presidents, Vice Presidents or Chief Officers (hereafter referred to as Executives) while eight were founders and majority owners of their own enterprises (hereafter referred to as Entrepreneurs). The research focused on the following 3 areas: 1) How top level managers really make strategic decisions in these two different parts of the world; 2) How Entrepreneurs and Executives differ, if at all, in their approach to strategic decision making when they combine analytical thinking with their intuition; 3) The similarities and differences in management skills and decision making routines between Entrepreneurs and Executives within the investigated management cultures.

Menedzsmentképességek és döntéshozatali közelítésmódok longitudinális elemzése a versenyképesség-kutatások alapján (Longitudinal analysis of management capabilities and decision making approaches based on the competitiveness researches)

Számos korábbi kutatás – köztük a szerzők korábbi vizsgálatai is – azt mutatja, hogy a menedzsmentképességek és a vállalatok versenyképessége között pozitív kapcsolat áll fenn, a jobban teljesítő és a proaktívabb vállalatok rendre felkészültebb, jobb vezetői képességekkel bíró, kockázatvállalóbb vezetőkkel rendelkeznek. Az is megfigyelhető, hogy az ebből a nézőpontból sikeresebben működő vállalatok döntéseiben az átlagosnál is erősebben érvényesül a racionális közelítésmód, melynek alkalmazásával a menedzserek az optimális cselekvési alternatíva kiválasztására törekszenek. A cikkben a szerzők az elmúlt 15 év versenyképességi kutatásainak tapasztalatait összegzik, kiemelt hangsúlyt helyezve a legfrissebb felmérés eredményeire. ________________ The article summarizes the main findings of the Competitiveness Research Program with respect to the skills and capabilities of the Hungarian managers and the decision making approaches they use during their work. The results of the four surveys conducted in 1996, 1999, 2004 and 2009 are fairly stable over time: practice minded behavior, professional expertise, and problem solving skills are on the top of the list of the most developed skills of the Hungarian executives. The rational approach is the most popular among the most widespread decision making models in the authors’ sample which is rather alarming since the present turbulent economic environment may demand more adaptive and intuitive approaches.