Workflow simulation for operational decision support

Simulation is widely used as a tool for analyzing business processes but is mostly focused on examining abstract steady-state situations. Such analyses are helpful for the initial design of a business process but are less suitable for operational decision making and continuous improvement. Here we describe a simulation system for operational decision support in the context of workflow management. To do this we exploit not only the workflow’s design, but also use logged data describing the system’s observed historic behavior, and incorporate information extracted about the current state of the workflow. Making use of actual data capturing the current state and historic information allows our simulations to accurately predict potential near-future behaviors for different scenarios. The approach is supported by a practical toolset which combines and extends the workflow management system YAWL and the process mining framework ProM.     

A decision support model for tax revenue collection in Greece

In the midst of the financial crisis currently unfolding in Greece, tax revenue collection is considered a top priority. This work describes a dynamic, Markov-based decision support model, aimed at predicting the behavior of a risk-neutral enterprise in Greece, and at evaluating tax policies before they are implemented. We use our model to i) analyze the effectiveness of an alternative taxation option periodically offered by the Greek government, ii) show that in the current environment, a rational enterprise has no incentive to disclose its profits, and iii) identify “virtuous” combinations of parameters which lead to full disclosure of profits.     

卫星系统作战效能评估辅助DSS研究

卫星系统作战效能评估是开发、使用和优化卫星系统的基础。从系统的角度探讨了卫星系统效能评估的方法论,建立并讨论了包括效能度量维、系统建模维和效能评估方法维的系统效能评估三维结构,在此基础上,提出了卫星系统作战效能评估辅助DSS的概念和结构,构建了卫星系统作战效能评估辅助DSS的模型体系,为科学、有效地进行卫星系统作战效能评估提出了新的途径,最后指出了深化效能评估的几个关键问题。     

A method for estimating the efficiency of the decision support system in handling crisis situations

A new method for estimating the efficiency of the decision support system in handling crisis situations is proposed. The method uses multiple-aspect analysis to direct the completion of the system under an automated regime.     

A decision support system for college selection

In this changing society the importance of higher education is increasing more than ever before. The selection of an appropriate university or college is of vital importance to the student for acquisition of proper educational experience. There are thousands of universities and colleges in the United States and Canada. The information available to students about each college is plentiful but is rather tedious to be obtained. The decision process of college selection is further complicated by many factors such as tuition, location, rank, size of the universities, and so forth. These factors play an important role in the final selection of a college. Therefore, a computer-based decision support system is developed in this paper to help users make better decisions in the selection of a college.

This college selection decision support system is designed to be menu-driven and highly user-friendly with a “Help” utility. Many “what-if” scenarios are also available in this system. It can be run on any IBM XT/AT or compatible machines with a DOS environment. It will allow users to make better decisions in their college selection process.     

A manufacturing decision support system for flamecutting

The design of a Manufacturing Decision Support System (MDSS) for the control of a flamecutting operation is discussed. The MDSS incorporates the overall economics of a continuing inventory. It also takes into account the use of left-over offcuts or partial plates, and the possibility of producing as a flow shop instead of on a job shop cut-to-order basis. Some research results are available that aid the construction of such a DSS; these are mostly in the areas of two-dimensional parts' layout and torch path sequencing. The proposed DSS constructs parts' nests, generates cutting sequences, directs the use of trim margins, and updates and outputs the economics of the whole cutting process. Its major strength is its potential use at the shop floor level, using relatively inexpensive computing power to control cutting torches that are usually driven by far more expensive systems that take much longer to determine layouts and cutting sequences.     

A decision support system for personnel scheduling in a manufacturing environment

A Decision Support System (DSS) is developed to support managers in the task of scheduling labor in the area of manufacturing. The DSS is designed to generate labor requirements by worker category and work center based on master production schedules. It is a PC-based, menu-driven program that generates a capacity plan based on data supplied by the user of the system.     

A decision support system for cellular manufacturing system design

With the growth of competitive pressure in the global markets, there has been an increase in demand in industry for cellular manufacturing systems (CMSs) in order to improve productivity and process flexibility. The design of CMSs for industrial applications is a complex and knowledge intensive process as it involves the consideration of many factors including production data and process characteristics. This paper describes the development and implementation of a decision support system for the feasibility and conceptual design of CMSs. The system is based on the knowledge-based system approach, and is able to make recommendations of system feasibility, cell formation techniques and cell types. A case study is also presented to demonstrate the capability of the decision support system.     

A decision support system for dynamic truck dispatching

The feasibility of developing and implementing a real-time Decision Support System (DSS) on a microcomputer to assist line managers in making decisions, which have many subjective and intangible constraints, is demonstrated. A dynamic truck dispatching system was chosen as a prototype example.

The results of the research presented here are twofold. First, insight was gained in how tasks should be divided between the computer and the human operator and in the required colorgraphics interface between them in complex decision making processes. Second, a prototype DSS for a real-time vehicle dispatching system was developed on a microcomputer based upon these insights. The DSS was designed to accommodate all the characteristics of a large corporation's national dispatch system using contract carriers.     

A decision support system for evaluating intangible investments

In this research project we have connected the procedural and substantive decision support by means of modern information technology. We have showed how the semistructured strategic decisions concerning intangible investments can be supported effectively by relating appropriate analysis methods to the different phases of the investment process. Because for the intangible investments there is no well-defined solution procedure available, a variety of methods must be integrated to support the solution process.

As a demonstrative example we showed how the intangible investments in logistic systems can be managed. It was highlighted that the logistics systems are complex, cross-functional systems that affect all major functions or departments within the firm beginning from the raw material deliveries and ending with the deliveries of finished goods. Investments in the logistics systems have corporatewide, cross-functional effects, and the investment decisions are strategic decisions. Consequently, the investments in the logistics systems should be strategically justified, not only cost-justified. The cross-functional effects imply that the investment analysis concerning the whole logistics system must be fulfilled under multiple, diversified criteria. We can not, however, ignore the financial, cost and revenue oriented, traditional investment criteria. They just have to be used in a new, flexible way in relation to the goals and objectives of the firm.

Strategic planning is a managerial area where semistructured problems frequently exist. One of the key problems faced in strategic management is the issue of investment decisions. Investments in information systems, logistic systems, flexible production systems, corporate image, etc, are examples of complex investment problems that are difficult to quantify and analyze with traditional techniques. Modern computer technology can enrich the analysis and improve the quality of strategic decision making.     

A fuzzy decision support system for credit scoring

Neural Computing and Applications - Credit score is a creditworthiness index, which enables the lender (bank and credit card companies) to evaluate its own risk exposure toward a particular...     

A decision support system for strategic asset allocation

Strategic asset allocation is a crucial activity for any institutional or individual investor. Given a set of asset classes, the problem concerns the definition and management over time of the best asset mix to achieve favorable returns subject to various uncertainties, policy and legal constraints, and other requirements. Although a considerable attention has been placed by the scientific community to address this problem by proposing sophisticated optimization models, limited effort has been devoted to the design of integrated framework that can be systematically used by financial operators. The paper presents a decision support system which integrates simulation techniques for forecasting future uncertain market conditions and sophisticated optimization models based on the stochastic programming paradigm. The system has been designed to be accessed via web and takes advantages of the increased computational power offered by high performance computing platforms. Real-world instances have been used to assess the performance of the decision support system also in comparison with more traditional portfolio optimization strategies.     

A decision support system for Evidence Based Medicine

We present a decision support system to let medical doctors analyze important clinical data, like patients medical history, diagnosis, or therapy, in order to detect common patterns of knowledge useful in the diagnosis process. The underlying approach mainly exploits case-based reasoning (CBR), which is useful to extract knowledge from previously experienced cases. In particular, we used sequence data mining to detect common patterns in patients histories and to highlight the effects of medical practices, based on evidence.We also exploited data warehousing techniques, such OLAP queries to let medical doctor analyze diagnosis along several measures, and recent visual data integration approaches and tools to effectively support the complex task of integrating and reconciling data from different medical data sources. In addition, due to massive presence of textual information within the clinical records of many hospitals, text mining techniques have been devised. In particular, we performed lexical analysis of free text in order to extract discriminatory terms and to derive encoded information. Finally, the system provides user friendly mechanisms to manage the protection of confidential medical data.System validation has been performed, mainly focusing on usability issues, by running experiments based on a large database from a primary public hospital.     

A decision support system for environmental effects monitoring

The Environmental Effects Monitoring (EEM) Statistical Assessment Tool (SAT) Decision Support System (DSS) has been developed to provide a user-friendly data analysis, display and decision support tool for Canada's federal environmental effects monitoring program for the pulp and paper and mining industries. The target users include industries, consultants, regional EEM coordinators, National EEM Office and scientists involved in EEM-related research. The tool allows the assessment of the effects of effluent from industrial or other sources on fish and benthic populations. Effect endpoints, which are used as indicators of potentially important effluent effects, are measured at effluent-exposed sites and are compared statistically to measures at reference sites, in order to determine if changes have occurred and the magnitude of the changes. The main driver of the EEM-SAT DSS is its rule-based expert system. The results are used in assessing the adequacy of existing regulations for protecting aquatic environments.     

Geographic information system based decision support systems for facility location, routing, and scheduling

Distribution management is concerned with the location of facilities, routing, and scheduling of vehicles and crews between the facilities to meet given objectives. Decision problems arising in distribution management are spatial in nature. This paper presents a method for the development of decision support systems based on geographic information systems for solving facility location and logistics problems.     

D-side: A facility and workforce planning group multi-criteria decision support system for Johnson Space Center

“To understand and protect our home planet, to explore the universe and search for life, and to inspire the next generation of explorers” is NASA's mission. The Systems Management Office at Johnson Space Center (JSC) is searching for methods to effectively manage the Center's resources to meet NASA's mission. D-Side is a group multi-criteria decision support system (GMDSS) developed to support facility decisions at JSC. D-Side uses a series of sequential and structured processes to plot facilities in a three-dimensional (3-D) graph on the basis of each facility's alignment with NASA's mission and goals, the extent to which other facilities are dependent on the facility, and the dollar value of capital investments that have been postponed at the facility relative to the facility's replacement value. A similarity factor rank orders facilities based on their Euclidean distance from Ideal and Nadir points. These similarity factors are then used to allocate capital improvement resources across facilities. We also present a parallel model that can be used to support decisions concerning allocation of human resources investments across workforce units. Finally, we present results from a pilot study where 12 experienced facility managers from NASA used D-Side and the organization's current approach to rank order and allocate funds for capital improvement across 20 facilities. Users evaluated D-Side favorably in terms of ease of use, the quality of the decision-making process, decision quality, and overall value-added. Their evaluations of D-Side were significantly more favorable than their evaluations of the current approach.     

Development of a decision support system for service delivery

Most traditional service delivery models were developed to solve single objective problems. While the disaster recovery task usually needed the consideration of multiple objectives (e.g. the total waiting time, the total weighted time of travelling, the fairness of resource distribution). Therefore, the traditional models can't completely support the disaster recovery task. In the real world, the assignments of service delivery are always performed by the vehicle dispatchers or truck drivers based on their experiences. However, the intuitive assignment methods are lacking a mathematic basis. They may be efficient but not necessarily effective. In order to provide an efficient and effective decision support system, this study has focused on the general expression of performances for service delivery and modifies the traditional delivery models by rule-inference techniques. The objective of this paper is to describe how a decision support system has been developed to achieve the performance requirement in emergency service delivery tasks, while traditional routing algorithms are modified and software techniques are utilized under a PC-based environment. Furthermore, some directions for future improvement are proposed.     

A decision support system for product design in concurrent engineering

Compared with the traditional sequential design method, concurrent engineering is a systematic approach to integrate concurrent design of products and their related processes. One of the key factors to successfully implement concurrent engineering is information technology. In order to design a product and its manufacturing process simultaneously, information on product features, manufacturing requirements, and customer demands must be processed while the design is concurrently going on. There is an increased understanding of the importance of the correct decisions being made at the conceptual design and development stages that involve many complex evaluation and decision-making tasks. In order to promote the efficiency in concurrent product development, appropriate evaluation and decision tools need to be provided. In this paper, the characteristics of fuzzy, multi-stage evaluation and decision making in concurrent product development process are analyzed and a decision support system for product design in concurrent engineering is presented. An example is given to illustrate the application of the system.     

Development of a decision support system for robot selection

With the availability of more different robot types and models along with their separate specifications, selecting the most appropriate robot is becoming more difficult and complicated for companies. Furthermore, a common set of robot selection criteria is not available for the decision makers. In this study, a two-phase robot selection decision support system, namely ROBSEL, is developed to help the decision makers in their robot selection decisions. In development of ROBSEL, an independent set of criteria is obtained first and arranged in the Fuzzy Analytical Hierarchy Process (FAHP) decision hierarchy. In the first elimination phase of the decision support system, the user obtains the feasible set of robots by providing limited values for the 15 requirements. ROBSEL, then, uses FAHP decision hierarchy to rank the feasible robots in the second phase. ROBSEL is illustrated and tested and several critical issues in its practical usage are explored in the paper. The applications of ROBSEL show that ROBSEL is a useful, practical and easy to use robot selection tool and improves robot selection decisions in the companies.