Using Simulation Systems for Decision Support

This chapter describes the use of simulation systems for decision support in support of real operations, which is the most challenging application domain in the discipline of modeling and simulation. To this end, the systems must be integrated as services into the operational infrastructure. To support discovery, selection, and composition of services, they need to be annotated regarding technical, syntactic, semantic, pragmatic, dynamic, and conceptual categories. The systems themselves must be complete and validated. The data must be obtainable, preferably via common protocols shared with the operational infrastructure. Agents and automated forces must produce situation adequate behavior. If these requirements for simulation systems and their annotations are fulfilled, decision support simulation can contribute significantly to the situational awareness up to cognitive levels of the decision maker

The engagement of expert opinions in the modeling of multi-attribute decision making for the selection of project delivery methods in building construction

Choosing the most appropriate project delivery method (PDM) available is acknowledged as a crucial issue in the construction industry. Both the choice and application of an unsuitable PDM can result in project failure. Likewise, the selection of a suitable PDM can increase the chance for project success. A method of selecting from among the seven PDMs recognized by the Construction Specifications Institute (CSI) was created in an attempt to address this issue. This research was comprised of three objectives. The first objective was to determine the influential factors needed to select the appropriate PDMs available to the US construction industry. The importance of each influential factor was also examined to determine whether or not significant differences exist between the following: both public and private sectors, project contractual parties, and various regions across the US. An empirical survey was conducted to gather this information throughout the US construction industry. The relative performance and suitability of PDMs for the different conditions involved in building constructions were evaluated as part of the second objective. Another empirical survey was conducted in the US construction industry to help with this evaluation. The performance and suitability of each PDM was examined with respect to 36 project criterion. The information was analyzed to create a decision support model for the PDM selection. This research used the early engagement of experts\u27 opinions in the modeling of multi-attribute decision making (MADM). A decision support model was established by linking together the Conjunctive Satisficing Method and the TOPSIS decision making approach, and applying them to the PDM selection. The face validation method, with a subset of the surveyed professionals, was used to validate the model. The results gathered from this research provide both the project owners and the decision makers with a framework that can be used to evaluate a project\u27s priorities and delivery options. A practical tool was also created that utilizes the expertise needed to make critical decisions without the physical existence of an expert panel. Applying the provided MADM model to the selection of a PDM allows the decision maker to choose the best alternative promoting a building construction project\u27s success --Abstract, page iv

Structuring the decision process : an evaluation of methods in the structuring the decision process

This chapter examines the effectiveness of methods that are designed to provide structure and support to decision making. Those that are primarily aimed at individual decision makers are examined first and then attention is turned to groups. In each case weaknesses of unaided decision making are identified and how successful the application of formal methods is likely to be in mitigating these weaknesses is assessed

Enhancing geographical information systems capabilities with multi-criteria evaluation functions

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A Data-informed Public Health Policy-Makers Platform

Hearing loss is a disease exhibiting a growing trend due to the number of factors, including but not limited to the mundane exposure to the noise and ever-increasing amount of older population. In the framework of a public health policymaking process, modeling of the hearing loss disease based on data is a key factor in alleviating the issues related to the disease issuing effective public health policies. First, the paper describes the steps of the data-driven policymaking process. Afterward, a scenario along with the part of the proposed platform, responsible for supporting policymaking are presented. With the aim of demonstrating the capabilities and usability of the platform for the policy-makers, some initial results of preliminary analytics are presented in a framework of a policy-making process. Ultimately, the utility of the approach is validated throughout the results of the survey which was presented to the health system policy-makers professionals involved in the policy development process in Croatia

RP Process Selection for Rapid Tooling in Sand Casting

The significant cycle-time improvements and geometrical capabilities of solid freeform fabrication systems have led to applications in sand casting industry for design verification and tooling. The time and cost effective deployment of rapid tooling processes using rapid prototyping technology has thus becoming an emerging area to be studied. To make full use of the advantages of rapid prototyping processes, the factors influencing the tooling approach must be identified and understood. This understanding is then used to develop a decision-making structure for RP process selection for rapid tooling in sand casting. In this manuscript we review our work in evaluating and building a framework for tooling process selection for sand castingMechanical Engineerin

Business intelligence systems and user's parameters: an application to a documents' database

This article presents earlier results of our research works in the area of modeling Business Intelligence Systems. The basic idea of this research area is presented first. We then show the necessity of including certain users' parameters in Information systems that are used in Business Intelligence systems in order to integrate a better response from such systems. We identified two main types of attributes that can be missing from a base and we showed why they needed to be included. A user model that is based on a cognitive user evolution is presented. This model when used together with a good definition of the information needs of the user (decision maker) will accelerate his decision making process

SOA-Driven Business-Software Alignment

The alignment of business processes and their supporting application software is a major concern during the initial software design phases. This paper proposes a design approach addressing this problem of business-software alignment. The approach takes an initial business model as a basis in deriving refined models that target a service-oriented software implementation. The approach explicitly identifies a software modeling level at which software modules are represented as services in a technology-platformindependent way. This model-driven service-oriented approach has the following properties: (i) there is a forced alignment (consistency) between business processes and supporting applications; (ii) changes in the business environment can be traced to the application and vice versa, via model relationships; (iii) the software modules modeled as services have a high degree of autonomy; (iv) migration to new technology platforms can be supported through the platform independent software model