A GIS-based multicriteria spatial decision support system for planning urban infrastructures

The planning of urban infrastructures has important spatial implications. The evaluation of alternative courses of action in this setting requires the explicit consideration of multiple criteria as they have important social, economic, and environmental effects. This paper presents a decision support system aimed at offering the users (e.g., government or municipal agencies) a flexible and user-friendly environment to provide decision aid in urban infrastructure planning. The visualization of available alternatives on maps provides a value-added for decision support processes in urban infrastructure evaluation problems. The development of this system has been motivated by a real world urban case study.     

A knowledge-based decision support system for shipboard damage control

The operational complexity of modern ships requires the use of advanced applications, called damage control systems (DCSs), able to assist crew members in the effective handling of dangerous events and accidents. In this article we describe the development of a knowledge-based decision support system (KDSS) integrated within a DCS designed for a national navy. The KDSS uses a hybrid design and runtime knowledge model to assist damage control operators through a kill card function which supports damage identification, action scheduling and system reconfiguration. We report a fire fighting scenario as illustrative application and discuss a preliminary evaluation of benefits allowed by the system in terms of critical performance measures. Our work can support further research aimed to apply expert systems to improve shipboard security and suggest similar applications in other contexts where situational awareness and damage management are crucial.     

Constructing a decision support system for management of employee turnover risk

In the time of knowledge economy, competency among enterprises is focused on the competency of human resources. Employee turnover risk is becoming an important facet influencing the stability and development of enterprises. After analyzing employee turnover risk factors that could threaten enterprise production and operations, we proposed a multi-level model of the evaluation system for employee turnover risk based on the analysis of factors influencing employee turnover risk. A decision support system is proposed for employee turnover risk management using message processing mechanisms and software combination technology and system integration. Data, information and knowledge needed in the system come from enterprises?? internal application systems and external systems. The structure and components of the system which is based on Web Services are presented. We also proposed an analytic system based on knowledge management. At last, strategies to effectively manage employee turnover risk are proposed.     

A simulation-based risk network model for decision support in project risk management

This paper presents a decision support system (DSS) for the modeling and management of project risks and risk interactions. This is a crucial activity in project management, as projects are facing a growing complexity with higher uncertainties and tighter constraints. Existing classical methods have limitations for modeling the complexity of project risks. For example, some phenomena like chain reactions and loops are not properly taken into account. This will influence the effectiveness of decisions for risk response planning and will lead to unexpected and undesired behavior in the project. Based on the concepts of DSS and the classical steps of project risk management, we develop an integrated DSS framework including the identification, assessment and analysis of the risk network. In the network, the nodes are the risks and the edges represent the cause and effect potential interactions between risks. The proposed simulation-based model makes it possible to re-evaluate risks and their priorities, to suggest and test mitigation actions, and then to support project manager in making decisions regarding risk response actions. An example of application is provided to illustrate the utility of the model.     

A computer-based system for risk management support

The scale and complexity of present day industrial operations involving hazardous substances are such that managers are faced with increasingly demanding decision problems. They must simultaneously consider technological, economic, environmental and sociopolitical factors. As a response to this problem a computer based decision support system is being developed to support risk management activities, with special emphasis given to hazardous chemicals. The IRIMS (Ispra Risk Management Support) system is an attempt to integrate a number of data bases, containing information relevant to risk management, with several existing simulation models which can be used to address problems of environmental assessment, risk analysis and system optimisation. The system is designed to be user friendly and results are displayed through high resolution colour graphics allowing the non specialised user to obtain a “feel” for the problem under investigation. The paper describes the current prototype system, which is geared to handle problems on a European scale, and plans for further developments which will allow more detailed studies on particular countries or regions.     

A knowledge based decision support system for computer performance management

Computer systems managers make decisions about hardware and software selection, performance evaluation, capacity planning, and other resource variables on the basis of factual data, accounting data, subjective judgements, and assumptions about the resource consumption of the jobs being run. The importance of computer resource planning calls for effective support methods. A Knowledge-Based DSS (KBDSS) will be able to assist managers in making these policy decisions by utilizing knowledge of the existing configuration and its capabilities, the organizational computing environment, available external resources, and their suppliers. Combining procedural and declarative methods, such a KBDSS may provide early warning of possible bottlenecks, forecast growth of hardware usage, and employ knowledge based inferencing to suggest suitable remedial actions to the systems manager. This paper presents a KBDSS for supporting computer resource planning decisions using a procedural/declarative framework, and illustrates the system's usage aspects.     

TITIM GIS-tool: A GIS-based decision support system for measuring the territorial impact of transport infrastructures

To achieve sustainability in the area of transport we need to view the decision-making process as a whole and consider all the most important socio-economic and environmental aspects involved. Improvements in transport infrastructures have a positive impact on regional development and significant repercussions on the economy, as well as affecting a large number of ecological processes.This article presents a DSS to assess the territorial effects of new linear transport infrastructures based on the use of GIS. The TITIM – Transport Infrastructure Territorial Impact Measurement – GIS tool allows these effects to be calculated by evaluating the improvement in accessibility, loss of landscape connectivity, and the impact on other local territorial variables such as landscape quality, biodiversity and land-use quality. The TITIM GIS tool assesses these variables automatically, simply by entering the required inputs, and thus avoiding the manual reiteration and execution of these multiple processes. TITIM allows researchers to use their own GIS databases as inputs, in contrast with other tools that use official or predefined maps.The TITIM GIS-tool is tested by application to six HSR projects in the Spanish Strategic Transport and Infrastructure Plan 2005–2020 (PEIT). The tool creates all 65 possible combinations of these projects, which will be the real test scenarios. For each one, the tool calculates the accessibility improvement, the landscape connectivity loss, and the impact on the landscape, biodiversity and land-use quality. The results reveal which of the HSR projects causes the greatest benefit to the transport system, any potential synergies that exist, and help define a priority for implementing the infrastructures in the plan.     

IA-SDSS: A GIS-based land use decision support system with consideration of carbon sequestration

Land use, land use change and forestry (LULUCF) can play a positive role in mitigating global warming by sequestering carbon from the atmosphere into vegetation and soils. Local entities (e.g. local government, community, stockholders) have been making great efforts in enhancing carbon sequestration (CS) of local forests for mitigating global climate change and participating in international carbon-trade promoted by the Kyoto Protocol. Approaches and tools are needed to assess the enhancement of CS through land use changes and proper policy decisions. This paper presents an integrated assessment framework and a spatial decision support system (IA-SDSS) as a tool to support land-use planning and local forestry development with consideration of CS. The IA-SDSS integrates two process-based carbon models, a spatial decision (EMDS) module, a spatial cost-benefit analysis (CBA) module, and the analytic hierarchy process (AHP) module. It can provide spatially explicit CS information as well as CS-induced economic benefits under various scenarios of the carbon credit market. A case study conducted in Liping County, Guizhou Province, China demonstrated that the IA-SDSS developed in this study is applicable in supporting decision-making on ‘where’ and ‘how’ to adopt forestry land use options in favor of CS.     

A multi-agent system for meteorological radar data management and decision support

The continuous processing and evaluation of meteorological radar data require significant efforts by scientists, both for data processing, storage, and maintenance, and for data interpretation and visualization. To assist meteorologists and to automate a large part of these tasks, we have designed and developed Abacus, a multi-agent system for managing radar data and providing decision support. Abacus' agents undertake data management and visualization tasks, while they are also responsible for extracting statistical indicators and assessing current weather conditions. Abacus agent system identifies potentially hazardous incidents, disseminates preprocessed information over the web, and enables warning services provided via email notifications. In this paper, Abacus' agent architecture is detailed and agent communication for information diffusion is presented. Focus is also given on the customizable logical rule-bases for agent reasoning required in decision support. The platform has been tested with real-world data from the Meteorological Service of Cyprus.     

GIS-based decision support for solar energy planning in urban environments

This paper describes the development of a solar energy planning system, consisting of a methodology and decision support software for planners and energy advisers. Intended primarily to predict and realise the potential of solar energy on an urban scale, the system will support decisions in relation to the key solar technologies: solar water heating, photovoltaics and passive solar gain. The prototype discussed here relates to the first of these. Based on a methodology for predicting the solar energy potential of domestic housing stock, it is implemented as a relational database application linked to a customised geographical information system (GIS). The methodology takes into account baseline energy consumption and projected energy saving benefits. To support this, the system incorporates a domestic energy model and addresses the major problem of data collection in two ways. Firstly, it provides a comprehensive set of default values derived from a new dwelling classification scheme that builds on previous research. Secondly, novel GIS tools enable key data to be extracted from digital urban maps in different operational modes. The paper concludes with a discussion of possible planning scenarios to illustrate how the system may be deployed at various levels of granularity to assist targeting of individual properties or city neighbourhoods, or for whole-city projections.     

Model management system for IRT-based test construction decision support system

Decision support system (DSS) has become widespread for some specific domains in recent years. However, DSS for IRT-based (item response theory) test construction has not yet been developed. This domain basically imposes a semi-structured or unstructured decision and, therefore, involves a very complex modeling process. This study develops a model management system (MMS) architecture to assist a non-expert user in manipulating test construction process efficiently and effectively. This architecture consists of four components: problem analysis, model type selection, model formulation and solver. The model type selection subsystem is further organized into three levels of hierarchy, i.e., environment, structure and parameter. A prototype is presented to demonstrate the feasibility of this architecture. The results indicate that this approach can be applied for providing an integrated, flexible and user-friendly DSS environment for producing better quality of results in less solution time.     

Development of medical decision support system for leukemia management

A prototype Medical Decision Support System (MDSS) for leukemia patients was developed with emphasis on total management approach from patient registration to diagnosis and treatment. Thus, the MDSS consists of four modules: registry, knowledge model, simulator, and Computer-Assisted Instruction (CAI). Integration of each module improves overall patient management capability and knowledge acquisition capability of the system. Four different knowledge models were developed to predict diagnosis: rule-based reasoning, case-based reasoning, neural network, and discriminant analysis. Among the four, rule-based reasoning produced the most accurate prediction in diagnosis. In the future, the method of leukemia registry can further be extended to the hospital-based cancer registry for other types of cancer. In order to be more effective, the registry should also be integrated with the hospital information system for an easier data entry.     

A decision support system for adaptive real-time management of seasonal wetlands in California

This paper describes the development of a comprehensive flow and salinity monitoring system and application of a decision support system (DSS) to improve management of seasonal wetlands in the San Joaquin Valley of California. The Environmental Protection Agency regulates salinity discharges from non-point sources to the San Joaquin River using a procedure known as the total maximum daily load (TMDL) to allocate the assimilative capacity of the river for salt among watershed sources. Management of wetland sources of salt load will require the development of monitoring systems, more integrative management strategies and coordination with other entities. To obtain local cooperation, the Grassland Water District (GWD), whose primary function is to supply surface water to private duck clubs and manage wetlands, needs to communicate to local landowners the likely impacts of salinity regulation on the long-term health and function of wildfowl habitat. The project described in this paper will also provide this information. The models that form the backbone of the DSS, develop salinity balances at both a regional and local scale. The regional scale concentrates on deliveries to and exports from the GWD while the local scale focuses on an individual wetland unit where more intensive monitoring is being conducted. The design of the DSS is constrained to meet the needs of busy wetland managers and is being designed from the bottom up utilizing tools and procedures familiar to these individuals.     

A microcomputer-based decision support system for the management of lumber mill production

Production management for a lumber mill includes the choice of saw patterns, as well as drying, sorting, grading and materials handling operations. The decision support system developed for an existing mill includes a linear programming (LP) model, data base software and a spreadsheet aid for detailed production scheduling. The LP model was structured to minimize total production cost subject to constraints on the available supply of raw material, the required output of timber, the available saw patterns and capacities on production facilities and materials handling operations. The LP solution is used by the spreadsheet support program to schedule product flow on a daily basis. The system was implemented on a microcomputer.     

A model‐driven decision support system for product risk analysis

Abstract: The paper describes a model‐driven decision support system for risk analysis in product development, based on an European Commission‐funded project. The model can be used to simulate the life cycle of a large batch of products and track products in operation and service phases with consideration of design and manufacturing phases. This provides some useful benefits – in particular, being able to generate composite results when the product life is subject to unpredictable events, which makes the system's behaviour non‐linear. A case study is conducted through a domestic appliance in the field trial from a manufacturing company, and the results indicate that the model can enable developers or manufacturers to understand the behaviour and characteristics of products or systems in the future use and to predict the cost of any changes in the pattern of their life.     

A decision support system for the technical sustainability assessment of water distribution systems

The purpose of this study is to develop a decision support system (DSS) for the technical sustainability assessment of water distribution systems (WDSs). The technical sustainability is assessed based on the sustainability index methodology using reliability, resiliency, and vulnerability as performance criteria. These performance criteria are visualized by the DSS combining several visualization techniques to improve the raw data readability and the effectiveness of the decision-making process. The technical sustainability of the existing WDS is assessed using the sustainability index methodology and two alternative scenarios are proposed to improve the sustainability. The “new pump” scenario is based on adding network components. The second scenario is based on using reclaimed water for non-potable water demand and fire flow. The results show that the DSS is effective to illustrate time-dependent variables in the WDS and that the sustainability index methodology is a credible approach to compare scenarios and to identify problematic locations.     

A decision support system for real-time order management in a heterogeneous production environment

In today's competitive market, many companies are morphing from the traditional new build, single brand, and silo environments to facilities accommodating diverse business missions. The later are called heterogeneous production environments in which the different business channels share their final production stage (shipping) to enable competitive advantages. In these production environments, at the operational level, the critical success factors are customer satisfaction, on-time delivery, product complexities, supply allocation, and resource utilization. At the strategic level, the success factors are revenue, customer urgency, and sales impact. This study proposes an End-to-End Customer Order Management System (E2E COMS) focusing on effective utilization of individual and shared resources to support real-time order management and mitigate risk of managing diverse missions. The proposed system consists of three integrated tools: Order Prioritization Tool (OPT) to assess and prioritize customer orders for each business channel, Order Fulfillment Progress Projection Tool (OFPPT) to predict the expected remaining order completion time considering inventory and resource capacity constraints, and risk mitigation tool to assess the risk of missing an order shipment due to shipping constraints. A real-time dashboard is developed to visualize the prioritized customer orders, expected time to arrive at the shipping area, shipping instructions, and two-dimensional risk assessment charts. The proposed system can effectively be used for shipping capacity management as well as prompt decision making.     

Using a decision support system in management education

The development of an innovative management decision support system in an educational context is described. Particular attention is devoted to the use of the system as an integral element of an MBA program and to the formal evaluation of the impact of the systems development process and the system on the users attitudes, values, information usage behavior and decision-making behavior.     

A knowledge-based decision support system for the management of parts and tools in FMS

Flexible manufacturing systems (FMS) are very complex systems with large part, tool, and information flows. The aim of this work is to develop a knowledge-based decision support system (KBDSS) for short-term scheduling in FMS strongly influenced by the tool management concept to provide a significant operational control tool for a wide range of machining cells, where a high level of flexibility is demanded, with benefits of more efficient cell utilization, greater tool flow control, and a dependable way of rapidly adjusting short-term production requirements. Development of a knowledge-based system to support the decision making process is justified by the inability of decision makers to diagnose efficiently many of the malfunctions that arise at machine, cell, and entire system levels during manufacturing. In this context, this paper proposes three knowledge-based models to ease the decision making process: an expert production scheduling system, a knowledge-based tool management decision support systems, and a tool management fault diagnosis system. The entire system has been created in a hierarchical manner and comprises more than 400 rules. The expert system (ES) was implemented in a commercial expert system shell, Knowledge Engineering System (KES) Production System (PS).