Point-of-use (POU) and point-of-entry (POE) water treatment are forms of decentralized water treatment that are becoming increasingly sought alternatives for ensuring the safety of drinking water. Although the acceptance of POU and POE systems is still the subject of some debate, it is generally acknowledged that they have a role to play in drinking water treatment. However, some of the main drivers for the increase in the use of POU and POE alternatives include: (1) the emergence of new technologies with high removal efficiencies of target contaminants; (2) the enhanced certification system of POU and POE treatment devices and components which ensures that devices have been well engineered to achieve defined contaminant removal targets and do not add contaminants from materials of construction; (3) the inclusion of POU and POE systems as acceptable means to comply with drinking water standards; and (4) the concerns voiced by consumers in several surveys regarding the safety of centrally treated drinking water; which, regardless of whether or not these concerns are justified, have led to an increase in the use of POU and POE treatment systems. With the commercialization of these devices the task of selecting a suitable device for treatment has become cumbersome. When the inherent complexity of a particular drinking water treatment task is added to the mix, a complex decision making situation is created. Thus the need for designing a decision support tool to compare and select POU and POE treatment systems was evident. Currently the best decision aid for selecting POU and POE systems is NSF International’s listing of the devices and their contaminant reduction claims. A significant contribution of this research is the depiction of an appropriate conceptual framework for developing usable and valid decision support systems (DSSs) to select or design water or wastewater treatment systems. A thorough investigation of the methods used to develop DSSs benchmarked a systematic approach to developing DSSs, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. Finally, it was concluded that there is a need to develop integrated DSSs that are generic, user-friendly and employ a systems analysis approach. Another significant contribution of this research is applying a systems analysis approach to outline aspects of implementation, management, and governance of POU and POE water treatment systems. The analysis also included a timeline of the progress of POU and POE treatment from regulatory, industry and certification, and research perspectives. Results of the analysis were considered the first step of a conceptual framework for the sustainability assessment of POU and POE treatment systems which acts as the basis for developing a decision support system that will help select sustainable POU or POE treatment systems. In the context of POU and POE treatment, sustainability encompasses providing: (a) safe drinking water to help maintain good human health and hygiene; (b) minimum negative impact on the environment; (c) better use of human, natural, and financial resources; (d) a high degree of functional robustness and flexibility; and (e) cultural acceptance thus encouraging responsible behavior by the users. The most significant contribution of this research is developing, for the first time, a set of sustainability criteria, objectives, and quantifiable indicators to properly assess the sustainability of the various POU and POE alternatives. Twenty five quantitative and qualitative indicators covering technical, economic, environmental, and socio-cultural aspects of implementing a POU or a POE system were defined. Results of a survey of experts’ judgment on the effectiveness of the developed list of indicators generated 52 comments from 11 experts, which helped in refining and enhancing the list. The conceptual framework for assessing the sustainability of POU and POE systems represented a blueprint for building the decision support system. Decision logic and cognitive thinking was used to formulate the calculation of the 20 refined indicators. The Analytical Hierarchy Process (AHP), a recognized Multi-criteria Decision Analysis (MCDA) tool, was employed to construct the structural hierarchy of sustainability indicators. Pairwise comparison was used to help in the analysis of indicators' relative importance and develop the indicators’ weights. A survey was designed to develop the relative weights of the indicators based on the average response of 19 stakeholders to a series of pairwise comparison questions pertaining to the relative importance of the indicators. Finally, the practical contribution of this research is the development of, for the first time, a new Decision Support System for Selecting Sustainable POU and POE Treatment Systems (D4SPOUTS) suitable for a particular water treatment case. The MCDA technique explained above is combined with designed screening rules, constraints, and case characteristics to be applied to a knowledgebase of POU and POE treatment systems incorporated in the DSS. The components of the DSS were built using Microsoft® Excel® and Visual Basic® for Applications. The quality of the DSS and aspects of its usability, applicability, and sensitivity analysis are demonstrated through a hypothetical case study for lead removal from drinking water. This research is expected to assist water purveyors, consultants, and other stakeholders in selecting sustainable and cost effective POU and POE treatment systems.

Semantic web based decision support systems represent domain knowledge using ontologies that capture the domain concepts, their relationships and instances. Typically, decision support systems use a single knowledge model—i.e. a single ontology—which at times restricts the knowledge coverage to only select aspects of the domain knowledge. The integration of multiple knowledge models—i.e. multiple ontologies—provides a holistic knowledge model that encompasses multiple perspectives, orientations and instances. The challenge is the execution-time merging of multiple ontologies whilst maintaining knowledge consistency and procedural validity. Knowledge morphing aims at the intelligent merging of multiple computerized knowledge artifacts—represented as distinct ontological models—in order to create a holistic and networked knowledge model. In our research, we have investigated and developed a knowledge morphing framework—termed as OntoMorph—that supports ontology merging through: (1) Ontology Reconciliation whereby we harmonize multiple ontologies in terms of their vocabularies, knowledge coverage, and description granularities; (2) Ontology Merging where multiple reconciled ontologies are merged into a single merged ontology. To achieve ontology merging, we have formalized a set of semantically-defined merging criteria that determine ontology merge points, and describe the associated process-specific and knowledge consistency constraints that need to be satisfied to ensure consistent ontology merging; and (3) Ontology Execution whereby we have developed logic-based execution engines for both execution-time ontology merging and the execution of the merged ontology to infer knowledge-based recommendations. We have utilized OWL reasoning services, for efficient and decidable reasoning, to execute an OWL ontology. We have applied the OntoMorph framework for clinical decision support, more specifically to achieve the dynamic merging of multiple clinical practice guidelines in order to handle comorbid situations where a patient may have multiple diseases and hence multiple clinical guidelines are to be simultaneously operationalized. We have demonstrated the execution time merging of ontologically-modelled clinical guidelines, such that the decision support recommendations are derived from multiple, yet merged, clinical guidelines such that the inferred recommendations are clinically consistent. The thesis contributes new methods for ontology reconciliation, merging and execution, and presents a solution for execution-time merging of multiple clinical guidelines.

The present study aims to develop an analysis package for combining forecasts that are obtained from different forecast methods. The package is composed of three modules, namely, the data input module, the data analysis module and the combination module. In data input module, the data is entered and saved as an Excel file with the given name. In data analysis module, the program computes the forecasts of the selected methods and displays the forecast results, the mean absolute errors, the mean square errors and the mean absolute percentage errors of these methods. In combination module, the forecast results, computed in the data analysis module, are combined according to the selected combination methods. All the detailed calculations of the forecasts and the values assigned by the program to minimize the mean absolute deviations, the mean square errors and the mean absolute percentage errors are displayed under the columns of the related method on the Excel spreadsheet of the file.

It is agreed upon by many researchers that, although risk management (RM) is accepted as one of the critical success factors for construction projects, project participants generally do not have sufficient knowledge pertinent to risk management concept and the number of risk management support tools which facilitate the process is rather low. In order to facilitate risk management activities, decision support tools that will enable risk identification, analysis and response strategy formulation should be developed. Decision support tools are necessary for systematic identification of risks, scenario generation, proactive management of risk and integration of risk management activities with other project management functions such as planning, cost estimating and monitoring project success. The aim of this study is to introduce a conceptual risk management model and a prototype risk management decision support system (DSS) which is applicable to construction projects. The proposed decision support system, namely Integrated Risk Management System (IRMS), is designed to support the user at all phases of the risk management process and to integrate risk management activities with other project management functions in the bid preparation stage of international construction projects. A risk management process model has been developed as well as a risk information model so that IRMS can be used for systematic management of risk by all parties involved in a construction project. Major functions of IRMS include, risk identification by using a built-in Hierarchical Risk Breakdown Structure (HRBS), risk analysis by Monte Carlo (MC) simulation, risk assessment by risk rating, risk re-assessment, response generation, risk monitoring and corporate memory. The applicability of the system has been tested by a real case study and its functionality has been demonstrated using the data associated with the case study.

In today&rsquo / s conditions, systems that surround individuals have evolved in structure such that, nature of variable interactions are much more complex and changing continuously. Logistics systems, which constitute an example for such systems, have also necessitated fast management and decision-making in a fast paced environment, under limited sources with the additional effect of increasing customer requirements and competition. These conditions require a dynamic analysis. In this study, system dynamics approach was shown to be a competent alternative to analyze complex and dynamic systems like logistics systems and its cost structure studied. A theoretical logistics model with a user interface is presented. Then the developed model implemented in an organization operating in aluminum industry by making the required modifications. A scenario analysis regarding a new investment decision studied. All analysis and modeling studies were carried out in Stella 6.0.1.

Subsequent to preparation of a valid base estimate for a construction project tender, it is required to add a bid markup on top of the base estimate. While an exaggerated bid markup weakens the competitiveness of the contractor, an underestimated one makes the contractor susceptible to financial losses. Therefore, an effective and reliable bid markup estimation method is indispensable to the success of a contractor both at the tender and the performance stages. The prevalent practice among contractors is to identify a certain percentage to add on the base estimate relying on their judgment without substantial ex! plicit support. In this thesis, a case based decision support system, which will count on the experience of the top experts of Turkish international contractors, will be constructed. Meanwhile, factors which are essential to bid markup estimation are to be identified.

In this study, a specific decision support system is designed and developed for Production Planning and Marketing Department of an apparel company. The developed system involves two modules with user friendly interface or data input and query. The system is designed to provide support in the following fields of decision making / pre cost estimation, capacity planning, master production planning and production scheduling. A detailed analysis of the existing system is conducted and Microsoft Access is used for the development of software. The cost and benefits of the implementing the system are also discussed in addition to basics, sample reports and the user interface of the developed program.

Truck transportation is considered as a favourable mode by shippers to carry freight at most ranges of distance as it has more flexibility in fleet size, capacity, scheduling, routing, and access. Although truck is considered as the popular mode for freight transportation, road-rail intermodal freight transportation becomes an attractive alternative to road only mode since the latter has no longer assured a reliable service due to traffic congestion problem. It also raises public concern in environmental and road safety impacts. Intermodal freight transportation is defined as a system that carries freight from origin to destination using two or more transportation modes where transfers between modes occur at an intermodal freight terminal. Success of the terminal depends on four major factors, namely: location, efficiency, financial sustainability, and rail level of service. Among these, the location is one of the most crucial success factors and needs to be considered carefully as it has direct and indirect impacts on a number of stakeholders including terminal users, terminal operators, transport network infrastructure providers, and community. Limitations of previous terminal location evaluation models in representing individual preference and behaviour as well as accommodating negotiation and communication between the players bring in an opportunity to develop a new model which is more flexible and capable of providing a solution that is not necessary to be optimal, but acceptable for every player without requiring explicit trade-offs. This thesis is aimed at demonstrating the feasibility of applying an agent-based approach to the evaluation of intermodal freight terminal location and investigating terminal effectiveness against stakeholder equity and some important aspects arising from the different stakeholders’ viewpoints. Agent technologies were introduced to model the stakeholders as individual agents. The agent concept was adopted to develop a decentralised location evaluation system that is able to balance the terminal effectiveness with the stakeholder equity. The proposed agent-based location evaluation model was modelled as a hierarchical control system that comprises three decision levels: local level, stakeholder level and policy level. Policy level is the highest decision level, which is represented by a policy maker. Apart from the policy level, the rest can be viewed as operational decision levels. Local level is the lowest control level. At this level, each stakeholder was classified into stakeholder groups based on their characteristics and interest. The terminal scenarios were then evaluated based on benefit maximisation criteria. Stakeholder control is the higher control level than the local level. It represents the control level where negotiations and decisions between groups of people (stakeholders) with different point of views are made. At this level, negotiation process was used to determine terminal location based on preference and equity of stakeholders. The determined terminal site was then used in the evaluation against constraints to ensure that all agents are satisfied. The terminal location decision for South East Queensland (SEQ) was applied as a case study of this thesis. The SEQ strategic freight transport model was developed, calibrated, and validated to assist in providing inputs for the evaluation of terminal location. The results indicated that for the developed agent-based location evaluation model, Yatala was selected as the most appropriate terminal location that results in the highest effectiveness and equity (as measured by level of satisfaction and Gini coefficient, respectively). Other location evaluation models were also used in comparison with the developed agent-based location evaluation model. Those include P-Median, P-Centre, and maximum covering models. It was found that the agent-based location evaluation model outperformed the other location evaluation models. Finally, a sensitivity analysis was conducted in order to evaluate the consistency of model outputs against the uncertainties in the input parameters. In most cases, the terminal location decisions obtained from the developed agent-based location evaluation model was not sensitive to the changes in those parameters. However, the results suggested that when a unit cost of truck travel delay increased, the impact on the final terminal location decisions was observed. This thesis demonstrated the feasibility of applying a decentralised approach to terminal location decision problem using a multi-agent concept and evaluating it against other well-known location problems. A new framework and methodology for the planning of intermodal terminal location evaluation was also formulated. Finally, the problems of terminal location evaluation and optimisation of intermodal freight terminal operation were integrated into a single evaluation model.

Abstract This thesis presents innovative applications of Multi-Objective Decision Support Systems (MODSS) to forestry decision support. New MODSS methodologies were developed to assess and evaluate forestry practices and finance regimes. The assessment of forestry investments draw on case studies conducted in the Hodgson Creek catchment on the Darling Downs in south Queensland and on the Atherton Tablelands in north Queensland, Australia. MODSS are systems that aid decision-making, in which a set of alternative management options are evaluated against a set of decision criteria. The criteria, that represent the stakeholders’ goals and objectives, are weighted to reflect stakeholder preferences regarding their relative importance. The weighted criteria scores are then aggregated to create an overall measure of option performance. In the first case study, MODSS procedures identified from the literature as being most suitable to forestry and the MODSS software package DEFINITE was used. After a critical review of the first study, a new MODSS was developed to address the particular needs of forestry evaluations and the weaknesses of current MODSS for addressing these needs. Limitations of the Hodgson Creek MODSS included lack of stakeholder engagement in the MODSS development process, inefficient use of the stakeholder time and an excessive work load on the experts in the scoring process. The new MODSS development process included the combined use of weighted sum and Electré aggregation methods, these being compensatory and non-compensatory aggregation methods. This combination of aggregation methods provided a measure of overall option performance and identified the presence of fatal flaws in the options. Various criteria weighting methods were trialled – including rank order methods, the analytical hierarchy process and direct assessments – to assess their utility for defining weights that reflected stakeholder priorities. A new hybrid weighting technique was developed using a combination of rank order methods and direct assessments. A new and innovative process for scoring options and criteria was developed, using an adaption of the Nominal Group Technique (NGT) in conjunction with a new computer-based Group Decision Support System (GDSS). This iterative process involved repeated rounds of individual scoring and group discussions. In the workshop conducted to elicit scores from experts, the GDSS was used to identify criteria where the elicited scores differed and discussions were focused on these criteria. After the discussions the options were rescored against the criteria and discussed further. This analysis was innovative in that uncertainty around the individual option scores was addressed for the first time using MODSS. This new application was developed in a spreadsheet using the risk analysis package @RISK. Evaluations of forestry options were undertaken at various time scales to address the long delay between incurring costs of tree planting and receiving returns from harvest. The various time scales identify the periods in which environmental and social benefits occurred as the trees grow and the economic benefits occurred at clearfell (or selective) harvest. This thesis specifically focuses on situations where measured and modelled data is not available, and seeks to increase the scientific rigour of the use of expert and stakeholder opinion in MODSS. The MODSS analyses revealed that forestry in the case study areas had the potential to offer considerable economic, environmental and social benefits to both landholders and the wider community. However, these benefits (and the associated costs) were not viewed as equally important. The MODSS developed in this study addressed these concerns. The benefits and costs of an option were reflected in its performance against the criteria. The degree of importance of the individual criteria varied from minor to high and overriding all other considerations. Criteria against which an option performed highly (the option’s strengths) were identified, as were criteria against which an option performed poorly (the option’s weaknesses). When these weaknesses occurred in highly important criteria, these were identified as fatal flaws in the option. The first case study in the Hodgson Creek catchment considered eight forestry options against 17 economic criteria, 12 environmental criteria and 12 social criteria. The second case study on the Atherton Tablelands considered 16 forestry options against eight economic criteria, six environmental criteria and five social criteria. The MODSS analysis identified the most preferred forestry options and the strengths and weaknesses of the options. In both case studies the most preferred options were large or medium-sized plantations with monoculture plantings with an element of non-landholder funding, in the form of government funding, joint ventures or land leasing agreements. These options had the highest performance against the economic criteria at all time scales and satisfactory environmental and social performance. Other forestry options that performed well included plantings focused on under-utilised land areas and salinity prevention areas, agroforestry, and selective harvesting of private native forest. These options generally had a higher level of performance against the social and environmental criteria, but lower levels of performance against economic criteria. These plantings would be undertaken for environmental and social reasons and not for financial returns. The application of MODSS developed in this thesis presents a significant scientific contribution to MODSS methodology. This thesis includes: the use of multiple time-periods to address the temporal differences in the delivery of benefits and costs, the use of NGT and a GDSS to provide a process for rapidly eliciting expert opinion, and the use of the combination of Electré and weighted sum aggregation methods to provide an overall measure of option performance and to identify fatal flaws in the options.

Abstract This thesis presents innovative applications of Multi-Objective Decision Support Systems (MODSS) to forestry decision support. New MODSS methodologies were developed to assess and evaluate forestry practices and finance regimes. The assessment of forestry investments draw on case studies conducted in the Hodgson Creek catchment on the Darling Downs in south Queensland and on the Atherton Tablelands in north Queensland, Australia. MODSS are systems that aid decision-making, in which a set of alternative management options are evaluated against a set of decision criteria. The criteria, that represent the stakeholders’ goals and objectives, are weighted to reflect stakeholder preferences regarding their relative importance. The weighted criteria scores are then aggregated to create an overall measure of option performance. In the first case study, MODSS procedures identified from the literature as being most suitable to forestry and the MODSS software package DEFINITE was used. After a critical review of the first study, a new MODSS was developed to address the particular needs of forestry evaluations and the weaknesses of current MODSS for addressing these needs. Limitations of the Hodgson Creek MODSS included lack of stakeholder engagement in the MODSS development process, inefficient use of the stakeholder time and an excessive work load on the experts in the scoring process. The new MODSS development process included the combined use of weighted sum and Electré aggregation methods, these being compensatory and non-compensatory aggregation methods. This combination of aggregation methods provided a measure of overall option performance and identified the presence of fatal flaws in the options. Various criteria weighting methods were trialled – including rank order methods, the analytical hierarchy process and direct assessments – to assess their utility for defining weights that reflected stakeholder priorities. A new hybrid weighting technique was developed using a combination of rank order methods and direct assessments. A new and innovative process for scoring options and criteria was developed, using an adaption of the Nominal Group Technique (NGT) in conjunction with a new computer-based Group Decision Support System (GDSS). This iterative process involved repeated rounds of individual scoring and group discussions. In the workshop conducted to elicit scores from experts, the GDSS was used to identify criteria where the elicited scores differed and discussions were focused on these criteria. After the discussions the options were rescored against the criteria and discussed further. This analysis was innovative in that uncertainty around the individual option scores was addressed for the first time using MODSS. This new application was developed in a spreadsheet using the risk analysis package @RISK. Evaluations of forestry options were undertaken at various time scales to address the long delay between incurring costs of tree planting and receiving returns from harvest. The various time scales identify the periods in which environmental and social benefits occurred as the trees grow and the economic benefits occurred at clearfell (or selective) harvest. This thesis specifically focuses on situations where measured and modelled data is not available, and seeks to increase the scientific rigour of the use of expert and stakeholder opinion in MODSS. The MODSS analyses revealed that forestry in the case study areas had the potential to offer considerable economic, environmental and social benefits to both landholders and the wider community. However, these benefits (and the associated costs) were not viewed as equally important. The MODSS developed in this study addressed these concerns. The benefits and costs of an option were reflected in its performance against the criteria. The degree of importance of the individual criteria varied from minor to high and overriding all other considerations. Criteria against which an option performed highly (the option’s strengths) were identified, as were criteria against which an option performed poorly (the option’s weaknesses). When these weaknesses occurred in highly important criteria, these were identified as fatal flaws in the option. The first case study in the Hodgson Creek catchment considered eight forestry options against 17 economic criteria, 12 environmental criteria and 12 social criteria. The second case study on the Atherton Tablelands considered 16 forestry options against eight economic criteria, six environmental criteria and five social criteria. The MODSS analysis identified the most preferred forestry options and the strengths and weaknesses of the options. In both case studies the most preferred options were large or medium-sized plantations with monoculture plantings with an element of non-landholder funding, in the form of government funding, joint ventures or land leasing agreements. These options had the highest performance against the economic criteria at all time scales and satisfactory environmental and social performance. Other forestry options that performed well included plantings focused on under-utilised land areas and salinity prevention areas, agroforestry, and selective harvesting of private native forest. These options generally had a higher level of performance against the social and environmental criteria, but lower levels of performance against economic criteria. These plantings would be undertaken for environmental and social reasons and not for financial returns. The application of MODSS developed in this thesis presents a significant scientific contribution to MODSS methodology. This thesis includes: the use of multiple time-periods to address the temporal differences in the delivery of benefits and costs, the use of NGT and a GDSS to provide a process for rapidly eliciting expert opinion, and the use of the combination of Electré and weighted sum aggregation methods to provide an overall measure of option performance and to identify fatal flaws in the options.