A web-based Decision Support System WebOptim for solving multiple objective optimization problems is presented. Its basic characteristics are: user-independent, multisolver-admissibility... Show More

A web-based Decision Support System WebOptim for solving multiple objective optimization problems is presented. Its basic characteristics are: user-independent, multisolver-admissibility, method-independent, heterogeneity, web-accessibility. Core system module is an original generalized interactive scalarizing method. It incorporates a number of thirteen interactive methods. Most of the known scalarizing approaches (reference point approach, reference direction approach, classification approach etc.) could be used by changing the method’s parameters. The Decision Maker (DM) can choose the most suitable for him/her form for setting his/her preferences: objective weights, aspiration levels, aspiration directions, aspiration intervals. This information could be changed interactively by the DM during the solution process. Depending on the DM’s preferences form the suitable scalarizing method is chosen automatically. In this way the demands on the DM’s knowledge and experience in the optimization methods area are minimized.

Sub-Surface Drilling is the process of making boreholes into the Earth, which can reach depths of many kilometers. One of the major purposes of such boreholes is the exploration of oil or gas... Show More

Sub-Surface Drilling is the process of making boreholes into the Earth, which can reach depths of many kilometers. One of the major purposes of such boreholes is the exploration of oil or gas bearing formations with the goal to recover the content of such reservoirs. Problems in drilling operations pose serious risks for the crew and the environment and can cause significant financial losses. Critical events usually do not arise abruptly, but develop over time before they escalate. In this work, the authors present a system that integrates sensor data and machine learning algorithms into a decision support system (DSS), thus helping to avoid critical events by monitoring and recommending preventive measures. The authors describe how the DSS is implemented as a distributed system and how data-driven decision support processes are implemented and integrated into the system. The DSS detects drilling operations by recognizing temporal patterns in the sensor data and uses a combination of detected operational rig-states and sensor data to predict and recommend preventive measures for the stuck pipe problem. The sensor data, detection results and predictions are distributed to all stakeholders and displayed in appropriate user interfaces.

In this paper, the authors propose to use Multi-Agents Systems (MAS) to model Cooperative Decision Support Systems (DSS). These systems support the collaboration of two kinds of agents: the human... Show More

In this paper, the authors propose to use Multi-Agents Systems (MAS) to model Cooperative Decision Support Systems (DSS). These systems support the collaboration of two kinds of agents: the human agent (the decision-maker or the user) and the artificial agent (machine) to solve jointly a problem and make a decision. In this way, the authors take advantage of the capacities of both the decision-maker and the machine. The novelty of the proposed approach is the modeling of Cooperative DSS using agent technology by coupling two MAS, the first is reactive and the latter is cognitive or deliberative. The resulting system is designed to support operators, as decision-makers during contingencies. Using the system, the operators should be able to: gather information about the incident location, access databases related to the incident, activate predictive modeling programs, support analyses, and monitor the progress of the situation and action execution. A simple scenario is given, to illustrate the feasibility of the proposal.

In the study at hand, the authors pose the question how people are influenced by olfactory stimulation while solving an economic problem? The economic problem involves managing a strategic planning... Show More

In the study at hand, the authors pose the question how people are influenced by olfactory stimulation while solving an economic problem? The economic problem involves managing a strategic planning simulation experiment. To demonstrate the fundamental task of economic decisions, the authors run experiments in the laboratory. The purpose of this paper is to analyze the relationship between several economic parameters and a firm’s success within a simulation experiment. Teams of students are assigned the role of managers of a firm within a competitive market situation. Subjects had the task of managing the complex situation in which they act in a group as managers to increase the performance of a firm by setting specific parameters. The authors will demonstrate to what extent a strong peppermint scent is able to influence the decision-makers within such a reasonably complex situation when they are to manage a firm's product range and compete against other firms. The authors are able to show that the smell of peppermint improved the overall mood considerably and thus also the results of the given task.