A direct decoupling approach for efficient reliability-based design optimization

This paper develops an efficient methodology to perform reliability-based design optimization (RBDO) by decoupling the optimization and reliability analysis iterations that are nested in traditional formulations. This is achieved by approximating the reliability constraints based on the reliability analysis results. The proposed approach does not use inverse first-order reliability analysis as other existing decoupled approaches, but uses direct reliability analysis. This strategy allows a modular approach and the use of more accurate methods, including Monte-Carlo-simulation (MCS)-based methods for highly nonlinear reliability constraints where first-order reliability approximation may not be accurate. The use of simulation-based methods also enables system-level reliability estimates to be included in the RBDO formulation. The efficiency of the proposed RBDO approach is further improved by identifying the potentially active reliability constraints at the beginning of each reliability analysis. A vehicle side impact problem is used to examine the proposed method, and the results show the usefulness of the proposed method.     

A human-centred methodology applied to decision support system design and evaluation in a railway network context

This article describes a methodological process for the design and evaluation of an interactive system in an industrial context. The process is called the U-model, and has been used in many projects since the early 1990s. The article describes a recent case study in which the U-model was adapted and used during a project involving the design of a decision support system intended for a railway investment context.

A decision support system for updating and incorporating climate change impacts into rainfall intensity-duration-frequency curves: Review of the stakeholder involvement process

Stakeholder involvement can serve to increase the quality of decision support systems (DSSs) and increase the perceived legitimacy of DSS outputs. Involving those who are ultimately affected by the outputs of DSSs in system design and development also reflects democratic principles. Importantly, stakeholder involvement can help ensure that the outputs of DSSs are used in decision-making processes. However, DSSs often fail due to poor engagement of stakeholder and end-user communities in the development and design of systems. The stakeholder engagement process applied in the development of the Computerized Tool for the Development of Intensity Duration Frequency Curves under Climate Change described here followed many of the tenants of best practices identified in the literature. While the engagement strategy was generally considered successful, over- and under-representation of some stakeholder groups and long term funding issues were weaknesses in the engagement process.     

Application of a spatial decision support system (SDSS) to reduce soil erosion in northern Ethiopia

A spatial decision support system (SDSS) based on multi-criteria and multi-objective decision analysis is applied in a case study in Ethiopia to reduce soil erosion on the basis of reallocation of crops according to their capacity to protect the soil. The case study is carried out in the Adwa district. The SDSS has been implemented using the widespread GIS software IDRISI 32 (release 2) and with the direct involvement of local stakeholders in defining factors and constraints. These are based on land cover-land use, altitude, potential erosion, proximity to roads, water and the relative soil protective capacity of each crop species. A reduction of soil loss from an average of 4.5 t ha⁻¹ yr⁻¹ to values below the risk threshold of soil degradation (1 t ha⁻¹ yr⁻¹) would be achieved through the application of the SDSS results. The biggest impediment to the reallocation exercise, however, is the shortage of cultivable land suitable for cultivation.     

A decision support system for the planning of the workload on a grain terminal

Ships, loaded with agricultural products, are handled by GEM at three different terminals in the port of Rotterdam. Each terminal consists of several berths and has both floating equipment and shore equipment. This paper describes the terminal system, the planning process and a menu driven computer planning model of the system. The planning model is split up into a first phase, in which berths are allocated, and a second phase, in which unloading equipment is assigned. The user of the model has the opportunity to manipulate several penalties and assign preferences to berths.     

A decision support system for design of mass production machining lines composed of stations with rotary or mobile table

This paper describes a decision support system (DSS) developed in order to offer to machining line designers a cognitive aid for early design stages. The aim of DSS is to assist the decision makers in finding the configuration of a new line that will meet quality and productivity requirements and minimize the investment costs. The current version of DSS is oriented to design of mass production machining lines composed of machines with rotary or mobile tables. This decision support system is based on mathematical models and methods which were devised to provide the designers with the optimal parameters of new line configuration including the required number of working stations of different types, the number of working positions at each station and spindle heads at each working position. The system is implemented under Autodesk Inventor and includes the modules for part modeling, process planning and machining system configuration. Its modular character and open architecture make upgrading with new mathematical tools suitable for other machining systems easy and fast. Moreover, it can be employed either as a separate software or integrated in a Product Life-cycle Management (PLM) tool.     

A knowledge-based decision support system for measuring the performance of government real estate investment

This paper describes a knowledge-based decision support system for measuring the performance of government real estate investment using DEA models. We propose an evaluation framework for real estate investment, including a database, a model base, and a knowledge base, to create a tool that a government can use to deal with decision-making problems via the Internet. This decision support system converts numerical data into information that can be used to evaluate possible real estate investments. Particularly, rules in the rule base are explained in more detail for illustrating the process of reasoning and KDSSGREI adapts quickly and accurately to infer and generate suggestions or actions. Data envelopment analysis (DEA) is used to perform efficiency analysis in this paper. Finally, we apply China's case to obtain strategies for reforming real estate investment.     

A model, a heuristic and a decision support system to solve the scheduling problem of an earth observing satellite constellation

China plans to launch four small optical satellites and four small SAR satellites to form a natural disaster monitoring constellation. Data can be obtained by the constellation in all weather conditions for disaster alert and environmental damage analysis. The scheduling problem for the constellation consists of selecting and timetabling the observation activities to acquire the requested images of the earth surface and scheduling the download activities to transmit the image files to a set of ground stations. The scheduling problem is required to be solved every day in a typical 1-day horizon and it must respect complex satellite operational constraints as well as request preferences, such as visibility time windows, transition time between consecutive observations or downloads, memory capacity, energy capacity, polygon target requests and priorities. The objective is to maximize the rewards of the images taken and transmitted. We present a nonlinear model of the scheduling problem, develop a priority-based heuristic with conflict-avoided, limited backtracking and download-as-needed features, which produces satisfactory feasible plans in a very short time. A decision support system based on the model and the heuristic is also provided. The system performance shows a significant improvement with respect to faster and better scheduling of an earth observing satellite constellation.     

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 strategic planning in large-scale marketing channels: An example in the tile industry

This paper presents a decision support system for strategic planning in marketing channels. A dynamic model of the marketing channel is employed which comprises manufacturer and retailer levels. Decision making is achieved through a game theoretical inference mechanism in which each player (manufacturer/retailer) optimises for a long-term profit maximisation objective. Both historical data and managerial expertise are used for the parameterisation of the system's knowledge base. The decision support system provides a forecast of profit and sales and computes pricing and shelf space allocation strategies that maximise long-term profit. It offers facilities such as the study of coalitions, long-term decision-making in all phases of a product's life cycle, the impact of pricing, allocation strategies, production expansion, cost regulation, and others. The operationality of the system is illustrated in decision-making situations in the tile industry.     

Bayesian inference in disputed authorship: A case study of cognitive errors and a new system for decision support

Bayesian inference provides a formal framework for assessing the odds of hypotheses in light of evidence. This makes Bayesian inference applicable to a wide range of diagnostic challenges in the field of chance discovery, including the problem of disputed authorship that arises in electronic commerce, counter-terrorism and other forensic applications. For example, when two documents are so similar that one is likely to be a hoax written from the other, the question is: Which document is most likely the source and which document is most likely the hoax? Here I review a Bayesian study of disputed authorship performed by a biblical scholar, and I show that the scholar makes critical errors with respect to several issues, namely: Causal Basis, Likelihood Judgment and Conditional Dependency. The scholar’s errors are important because they have a large effect on his conclusions and because similar errors often occur when people, both experts and novices, are faced with the challenges of Bayesian inference. As a practical solution, I introduce a graphical system designed to help prevent the observed errors. I discuss how this decision support system applies more generally to any problem of Bayesian inference, and how it differs from the graphical models of Bayesian Networks.     

A decision support system based on fuzzy reasoning and AHP–FPP for the ecodesign of products: Application to footwear as case study

The design stage represents one of the most critic steps for product development. Here, a great number of considerations have to be borne in mind, e.g., technical, functional, aesthetic or economic criteria. More recently, the increasing concerns on environmental aspects have added complexity to the process, known as ecodesign. In this respect, a framework to integrate the criteria provided by quantitative environmental indicators has been proposed on the basis of Fuzzy Preference Programming method features and fuzzy logic reasoning. As a result, an integrated Ecodesign Index (EcoInd) is obtained. This idea enables the decision making at process and product level taking into account different indicators at a time. The ecodesign of children's footwear was taken as case study and an ecodesign tool (decision support system) that included the estimation of environmental indicators and their integration was developed. Different models of shoes were analyzed to identify the most environmentally friendly design and to test the tool. In this case, the Ecological Footprint and two Environmental Risk Assessment indicators, namely Hazard Quotient and Cancer Risk, were selected as relevant environmental indicators and they were computed from data provided by a shoes manufacturer. Then, these indicators were integrated in the ecodesign tool and the EcoInd values were appraised for the children's footwear models analyzed. According to these figures, they were ranked as Red Leather > White Leather > White Synthetic > Pink Synthetic, from best to worst.