A system for decision support without explicit objective functions

This paper presents a conversational decision support system: Resource Allocation in Business Operation under Uncertain Worth (RAINBOW). The focus is placed on the loosely structured decision situation where the multiple objective functions are given only implicitly and should be locally approximated by the decision maker as the decision making process proceeds. Basically, RAINBOW supports the process of convergence to a preferred alternative by giving the decision maker information which will help him form consistent evaluations of the utility function, the objective functions and the solution for the decision problem.     

A decision support system for optimising the order fulfilment process

Many authors have highlighted gaps at the interfaces between supply chains (SCs) and demand chains. Generally, the latter tends primarily to be ‘agile’ by maximising effectiveness and responsiveness while the former tends to be ‘lean’ by maximising efficiency. When, in the SC, disruptions (that lead to stock-out situations) occur after customer orders have been accepted, managers are faced with the problem of maximising customer satisfaction while taking into consideration the conflicting objectives of the supply and demand sides of the order fulfilment process. This article proposes a cross-functional multi-criteria decision-making (advanced available-to-promise) tool that provides different strategic options from which a solution can be chosen. It also proposes a performance measurement system to support the decision-making and improvement process. The results of some experimental tests show that the model enables to make strategic decisions on the degree of flexibility required to achieve the desired level of customer service.     

A decision support tool for planning bills-of-material

In this paper, the framework for a decision support tool for planning bills-of-material is presented. This tool generates a set of modular planning bills-of-material from the manufacturing bills-of-material for a company. The tool attempts to consolidate options in a product family which are specific. The force with which the tool attempts to consolidate two or more options is dependent on the financial control parameters. As well as having a minimum amount of common material, the financial value of such a match must also be of sufficiently high value to be worth planning together. The tool also examines the long-term inventory effect of planning two or more options as common.     

A decision support system for a third-party coordinator managing supply chain with demand uncertainty

Global supply chains reduce cost but increase lead times, complexities and uncertainties. Retailers in consumer products industry are getting shorter lead time to respond to market demand. To meet this challenge, many rely on third party supply chain managers (SCMs) for economically supplying required quantities of finished products quickly. However, due to shorter ‘time to market’, the SCM has to procure raw materials and start production process based on expected demand. Since SCM absorbs financial penalties associated with under- and over-estimation of demand from retailer, finding an optimal production lot size and product customisation strategy are essential to an SCM's operation. We develop a profit maximisation model and provide a close-form solution that allows an SCM to calculate optimal production lot size. The model is used to examine profitability of postponing product customisation. Finally, the effect of demand variation on SCM's profitability is explored.     

Du pont decision support system (DSS) for expenditure budgeting

The objective of this project is to develop a decision support system (DSS) for expenditure budgeting. The system will support current expenditure budgeting according to the same principles as the fixed expenditure (capital) budgeting. The framework of the analysis is based on an ex ante version of the traditional (ex post) du Pont system presenting the profitability of the firm as a function of asset turnover and profit margin. The present approach depicts the relationships between sales and the alternative classes of expenditure, expenses and assets by means of a mathematical model expressed as a DSS in an EXCEL spreadsheet framework. The model assumes that the average absorption time and revenue lag structure for expenditure classes are constant in time. However, the monetary productivity of expenditures is a second-order parabola of the amount of expenditure. The use of the model is demonstrated in two illustrative cases (SIEMENS and ABB) using published financial statement data. The estimation of the revenue function is based on an interactive analysis and simulation with past data.     

A decision support system for the selection of a casting process using analytic hierarchy process

This paper presents an Analytic Hierarchy Process (AHP) based decision support system to select the most suitable casting process for a given product. The hierarchical structure of the proposed method allows the decision maker to compare the different casting processes using the material suitability and flexibility, geometrical complexity, dimensional tolerance and surface finish of the casting, and the cost as the criteria for selection. Judgemental inconsistency of the decision maker in selecting the casting process is taken care by ensuring that the value of consistency ratio is below (0.1). A numerical example is presented to illustrate the effectiveness of the proposed methodology for selecting the suitable casting process.     

基于神经网络的期货套期保值决策支持系统

针对期货套期保值业务的特点 ,分析了期货套期保值决策支持系统的整体逻辑 ,尝试用人工神经网络专家系统预测期货行情走势 ,介绍了如何将期货市场与 BP网络有机结合起来构造适合期价预测的模型 ,并且在实证分析中给出了寻找最优预测效果的方法以及预测结论应用分析 .同时 ,提出了以此分析为基础的 DSS系统结构和功能 ,对辅助套期保值者决策有一定的指导意义     

A decision support methodology for strategic planning in maritime transportation

This paper presents a decision support methodology for strategic planning in tramp and industrial shipping. The proposed methodology combines simulation and optimization, where a Monte Carlo simulation framework is built around an optimization-based decision support system for short-term routing and scheduling. The simulation proceeds by considering a series of short-term routing and scheduling problems using a rolling horizon principle where information is revealed as time goes by. The approach is flexible in the sense that it can easily be configured to provide decision support for a wide range of strategic planning problems, such as fleet size and mix problems, analysis of long-term contracts and contract terms. The methodology is tested on a real case for a major Norwegian shipping company. The methodology provided valuable decision support on important strategic planning problems for the shipping company.     

Planning for strategic decision support systems

The emergence of Strategic Decision Support Systems has opened up new vistas for the true integration of formal models into the strategic planning process. However, with these new opportunities also come the need to develop planning mechanisms that will permit these sophisticated systems to achieve their potential. The process of strategic planning for Strategic Decision Support Systems that is described in this article serves to cast the organization's overall plans, strategies and strategic attributes into a framework that can be used to develop formal SDSS plans.     

Multicriteria decision support for global e-government evaluation

E-government refers to the use of information and communication technologies (ICT) by governments to provide digital services to citizens and businesses over the Internet, at local, national or international level. Benchmarking and assessing e-government is therefore necessary to monitor performance and progress by individual countries and identify areas for improvement. Although such measurements have already been initiated by various organizations, they scarcely highlight the multidimensional nature of the assessment. This paper outlines a multicriteria methodology to evaluate e-government using a system of eight evaluation criteria that are built on four points of view: (1) infrastructures, (2) investments, (3) e-processes, and (4) users’ attitude. The overall evaluation is obtained through an additive value model which is assessed with the involvement of a single decision maker–evaluator and the use of a multicriteria ordinal regression approach. Specifically, the UTA II method is used, whose interactive application process is divided in two phases. Its implementation is supported by MIIDAS (multicriteria interactive intelligent decision aiding system). This research work aims at supporting potential stakeholders to perform a global e-government evaluation, based on their own viewpoints and preferences. Finally, 21 European countries are evaluated and ranked considering the latest criteria data.     

User cognitive types for decision support systems

This paper describes and presents the results of an experiment that was used to investigate the relationships between cognitive types, information presentation and their effect on decision making performance within the context of an MIS/DSS. The experimental task required subjects to specify production levels for future periods given information on prior results. Ninety-six subjects performed the experiment, with 24 in each of the four Jungian cognitive type groups. All subjects received the same information for making decisions but different information presentation modes. The information presentation modes included raw and statistically summarized data and graphical and tabular layouts. The subjects were provided their results after each of their ten decision ‘runs’ via hard copy output. Decisions were entered at CRT terminals by the subjects. Experimental results demonstrated significant differences in performance by cognitive types. Decision performance rankings were partially supported by the results. Hypothesized pairings of cognitive types and information presentation modes were also partially supported. Implications of the results for MIS/DSS design are explored.     

Engineering of a decision support system for underground coal mine planning and production scheduling

This paper reports on the development of a computer-based management information system at Datong Coal Company, the largest subsidiary of China National Coal Corporation. Particularly presented is the development methodology of a decision support system for underground coal mine planning and production scheduling, including an integration of computer graphics, database management, mathematical modelling and knowledge engineering techniques and a coupling of life cycle and prototyping software engineering processes to support systems quality assurance.     

The state of decision support systems: A review

Many organisations are now realising that information technology can make a significant contribution to their operations. Recent developments in decision support software are such that the time may have come when information technology will contribute significantly to managerial decision-making. This paper considers these developments alongside the organisational issues involved in decision-making, and the current position of IT in many mature organisations. The conclusion is that the new range of decision support software, whilst opening up further areas for computerised decision support, is unlikely to compete successfully for corporate IT funds. Use of the new tools will be restricted to small, isolated applications.     

A decision support approach for two-stage multi-objective index tracking using improved lagrangian decomposition

We present a decision support approach for a network structured stochastic multi-objective index tracking problem in this paper. Due to the non-convexity of this problem, the developed network is modeled as a Stochastic Mixed Integer Linear Program (SMILP). We also propose an optimization-based approach to scenario generation to protect against the risk of parameter estimation for the SMILP. Progressive Hedging (PH), an improved Lagrangian scheme, is designed to decompose the general model into scenario-based sub-problems. Furthermore, we innovatively combine tabu search and the sub-gradient method into PH to enhance the tracking capabilities of the model. We show the robustness of the algorithm through effectively solving a large number of numerical instances.     

Strategic group decision support systems--a guide for the unwary

Considerable interest is currently being shown in the use of information technology to assist in improving group process, particularly those associated with strategic planning. Three major approaches are developing to provide this support, and these are described in this article. In general, articles about Group DSS are overwhelmingly favourable to the approaches, although research findings suggest that some forms of Group DSS can have deleterious effects on the quality of meetings. These research findings are discussed.     

A decision support system for modelling and implementing the supply network configuration and operations scheduling problem in the machine tool industry

This paper presents a decision support system to simultaneously solve the supply network configuration problem and the operations scheduling problem for the machine tool industry. A novel database structure, which is able to consider alternative operations and alternative bills of material, has been used. An algorithm for complete enumeration to determine all the feasible solutions using stroke graphs is introduced. A multiagent-based simulator evaluates the different key performance indicators that the supply network deals with for each alternative solution (e.g. workload, profits, delivery times, etc.) to determine that ‘satisficed’ by the collaborative decision-making among its members. A case study based on a Spanish company that assembles highly customised machines and tools in several European plants is considered. From the experiments results based on data linked to this industry, it will be demonstrated that the tool is potentially useful for stakeholders and for the central decision-maker to make decisions collaboratively in a multisite context case.     

Multi-criteria decision support and evaluation of strategies for nuclear remediation management

Environmental emergency situations can differ in many ways, for instance according to their causes and the dimension of their impacts. Yet, they share the characteristic of sudden onset and the necessity for a coherent and effective emergency management. In this paper we consider decision support in the event of a nuclear or radiological accident in Europe. RODOS, an acronym for real-time on-line decision support system, is a decision support system designed to provide support from the early phases through to the medium and long-term phases. This work highlights the role of multi-criteria decision analysis (MCDA) within RODOS in ensuring the transparency of decision processes within emergency and remediation management. Special emphasis is placed on the evaluation of alternative remediation or countermeasure strategies using the multi-criteria decision support tool Web-HIPRE in scenario focused decision making workshops involving different stakeholder and expert groups. Decision support is enhanced by a module that generates natural language explanations to facilitate the understanding of the evaluation process, therefore contributing to the direct involvement of the decision makers, with the aim of increasing their confidence in the results of the analyses carried out, forming an audit trail for the decision making process and improving the acceptability of the system as a whole.     

An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming

In this paper, we present an aggregate production planning (APP) model applied to a Portuguese firm that produces construction materials. A multiple criteria mixed integer linear programming (MCMILP) model is developed with the following performance criteria: (1) maximize profit, (2) minimize late orders, and (3) minimize work force level changes. It includes certain operational features such as partial inflexibility of the work force, legal restrictions on workload, work force size (workers to be hired and downsized), workers in training, and production and inventory capacity. The purpose is to determine the number of workers for each worker type, the number of overtime hours, the inventory level for each product category, and the level of subcontracting in order to meet the forecasted demand for a planning period of 12 months. Additionally, a decision support system (DSS) based on the MCMILP model is proposed. It will help practitioners find the “best” solution for an APP problem without having to familiarize themselves with the mathematical complexities associated with the model. An example to illustrate the use of the DSS is also included.