Decision support tool for production planning of a machining line

A decision support tool for production planning was developed to perform the difficult and time consuming task of allocating resources within the industrial partner's machining line, consisting of identical Computerized Numerically Controlled machines. The production-planning tool identified significant labour savings in a number of the industrial partner's production plans.

Multi-criteria content adaptation service selection broker

In this paper, we propose a service-oriented content adaptation framework and an approach to the Content Adaptation Service Selection (CASS) problem. In particular, the problem is how to assign adaptation tasks (e.g., transcoding, video summarization, etc) together with respective content segments to appropriate adaptation services. Current systems tend to be mostly centralized suffering from single point failures. The proposed algorithm consists of a greedy and single objective assignment function that is constructed on top of an adaptation path tree. The performance of the proposed service selection framework is studied in terms of efficiency of service selection execution under various conditions. The results indicate that the proposed policy performs substantially better than the baseline approach.

Generalized Bonferroni mean operators in multi-criteria aggregation

In this paper we provide a systematic investigation of a family of composed aggregation functions which generalize the Bonferroni mean. Such extensions of the Bonferroni mean are capable of modeling the concepts of hard and soft partial conjunction and disjunction as well as that of k-tolerance and k-intolerance. There are several interesting special cases with quite an intuitive interpretation for application.

Decision support in interest based negotiation support systems: the AssetDivider system

Negotiation Support Systems (NSS) model the process of negotiation from basic template support to more sophisticated decision making support. The authors attempt to develop systems capable of decision support by suggesting possible solutions for the given dispute. Current Negotiation Support Systems primarily rely upon mathematical optimisation techniques and often ignore heuristics and other methods derived from practice. This chapter discusses the technology of several negotiation support systems in family law developed in their laboratory based on data collected and methods derived from practise. The chapter explores similarities and differences between systems the authors have created and demonstrates their latest development, AssetDivider.

Managing negotiation knowledge with the goal of developing negotiation decision support systems

While Information Technology has been used to support negotiation there is little research in the domain of knowledge management in legal negotiation. In this paper we discuss the nature of negotiation knowledge and how such knowledge can be utilized to construct negotiation decision support systems. We conduct an in-depth examination of the notion of a BATNA (Best Alternative to a Negotiated Agreement) and given a useful BATNA, how we can use issue and preference elicitation and compensation and trade-off strategies to provide negotiation decision support. We conclude by indicating how current negotiation support systems can be extended to support Online Dispute Resolution and haw we can extend the Family_Winner system in light of the need to more adequately manage negotiation knowledge.

Trade-off manipulations in the development of negotiation decision support systems

Our model of negotiation for constructing Negotiation Decision Support Systems is based upon Principled Negotiation and uses trade-off manipulations in order to provide decision support. A resulting system, Family_Winner, was constructed using several information systems techniques. Trade-off Maps (a variant of Constraint Diagrams) are used to represent trade-off opportunities, while an empirically derived formula calculates the amount of compensation given to the ratings of issues remaining in dispute. The Issue Decomposition Hierarchy embedded in the system allows for the incorporation of sub-issues. Family_Winner was originally built for use in Australian Family Law. We believe our model can be extended for use in various other domains.

Family_Winner has been evaluated in the areas of industrial relations, international disputation and company disputes. Results from our evaluation suggest the system works satisfactorily in these domains. We conclude this paper by describing future projects that will develop and extend Family_Winner's functions and applicability.

Developing negotiation decision support systems that support mediators : a case study of the Family_Winner system

Negotiation Support Systems have traditionally modelled the process of negotiation. They often rely on mathematical optimisation techniques and ignore heuristics and other methods derived from practice. Our goal is to develop systems capable of decision support to help resolve a given dispute. A system we have constructed, Family_Winner, uses empirical evidence to dynamically modify initial preferences throughout the negotiation process. It sequentially allocates issues using trade-offs and compensation opportunities inherent in the dispute.

Virtual melawati : 3D GIS as a decision support tool for urban planning

Virtual Melawati is an environment for developing expertise in the application of 3D interactive visualization and GIS (Geographic Information System) to address problems of the built environment and to test the model as a decision support tool in the context of the local planning authorities in Malaysia. The visual approach enables the integration of highly complex spatial GIS information such as the evolution and transformation of the urban precinct as well as the impact of planned developments into the decision making process. The study will examine the techniques of data acquisition, data reconstruction from physical to digital, urban analysis and visualization in constructing an interactive 3D GIS model to support and assist the decision making process in urban design and planning. The outcomes of the study will deliver an experimental test bed for improving decision making processes in urban planning and design utilizing 3D modeling and GIS. The project will accelerate the uptake of digital and multimedia methods in local government, facilitate current planning and consultation processes between councils and stakeholders and improve the dissemination and management of spatial information about urban environments.

An Intelligent Human-Computer Interaction System for Decision Support

This paper proposes a novel architecture for
developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be
incorporated into a computerized system and, at the same time, to
preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking
process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first
employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed
approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.

A fuzzy decision support method for customer preferences analysis based on Choquet integral

The explosion of the Web 2:0 platforms, with massive volume of user generated data, has presented many new opportunities as well as challenges for organizations in understanding consumer's behavior to support for business planning process. Feature based sentiment mining has been an emerging area in providing tools for automated opinion discovery and summarization to help business managers with achieving such goals. However, the current feature based sentiment mining systems were only able to provide some forms of sentiments summary with respect to product features, but impossible to provide insight into the decision making process of consumers. In this paper, we will present a relatively new decision support method based on Choquet Integral aggregation function, Shapley value and Interaction Index which is able to address such requirements of business managers. Using a study case of Hotel industry, we will demonstrate how this technique can be applied to effectively model the user's preference of (hotel) features. The presented method has potential to extend the practical capability of sentiment mining area, while, research findings and analysis are useful in helping business managers to define new target customers and to plan more effective marketing strategies.