Combining prospect theory and fuzzy numbers to multi-criteria decision making

Many multi-criteria decision making (MCDM) methods have been proposed to handle uncertain decision making problems. Most of them are based on fuzzy numbers and they are not able to cope with risk in decision making. In recent years, some MCDM methods based on prospect theory to handle risk MCDM problems have been developed. In this paper, we propose a hybrid approach combining prospect theory and fuzzy numbers to handle risk and uncertainty in MCDM problems. So, it is possible to tackle more challenging MCDM problems. A case study involving oil spill in the sea illustrates the application of the novel method.     

Using argumentation to model agent decision making in economic experiments

In this paper we demonstrate how a qualitative framework for decision making can be used to model scenarios from experimental economic studies and we show how our approach explains the results that have been reported from such studies. Our framework is an argumentation-based one in which the social values promoted or demoted by alternative action options are explicitly represented. Our particular representation is used to model the Dictator Game and the Ultimatum Game, which are simple interactions in which it must be decided how a sum of money will be divided between the players in the games. Studies have been conducted into how humans act in such games and the results are not explained by a decision-model that assumes that the participants are purely self-interested utility-maximisers. Some studies further suggest that differences in choices made in different cultures may reflect their day to day behaviour, which can in turn be related to the values of the subjects, and how they order their values. In this paper we show how these interactions can be modelled in agent systems in a framework that makes explicit the reasons for the agents’ choices based upon their social values. Our framework is intended for use in situations where agents are required to be adaptable, for example, where agents may prefer different outcome states in transactions involving different types of counter-parties.     

A visualization tool to support decision making in environmental and biological planning

Large-scale ecosystem management involves consideration of many factors for informed decision making. The EverVIEW Data Viewer is a cross-platform desktop decision support tool to help decision makers compare simulation model outputs from competing plans for restoring Florida's Greater Everglades. The integration of NetCDF metadata conventions into EverVIEW allows end-users from multiple institutions within and beyond the Everglades restoration community to share information and tools. Our development process incorporates continuous interaction with targeted end-users for increased likelihood of adoption. One of EverVIEW's signature features is side-by-side map panels, which can be used to simultaneously compare species or habitat impacts from alternative restoration plans. Other features include examination of potential restoration plan impacts across multiple geographic or tabular displays, and animation through time. As a result of an iterative, standards-driven approach, EverVIEW is relevant to large-scale planning beyond Florida, and is used in multiple biological planning efforts in the United States.     

Multi‐agent distributed intelligent system based on fuzzy decision making

Generally decision making for solving ill‐structured problems in DSS takes place in uncertain situations. The main drawbacks of existing traditional DSS are inefficiencies associated with dealing with complex models and large databases. Usually a fuzzy DSS has many input variables and, hence, its knowledge base, containing the totality of fuzzy rules, is very large. Large rule base leads to disadvantages in speed, reliability, and complexity of DSS. This paper introduces an alternative concept for designing fuzzy DSS based on multi‐agent distributed artificial intelligent technology and fuzzy decision making. The main idea of the proposed DSS is based on granulation of the overall system intelligence between cooperative autonomous intelligent agents capable of competing and cooperating with each other in order to propose a total solution to the problem and organization (combining individual solutions) of the proposed solution into the final solution. It is supposed that every agent in DSS is characterized by a set of fuzzy criteria of unequal importance and definition of a “winner” agent is based on multi‐criteria fuzzy decision making involving unequal objectives. © 2000 John Wiley & Sons, Inc.     

Online decision making and automatic decision model adaptation

The paper investigates an online version of the vehicle routing problem with time windows, in which additionally arriving requests cause the revision of so far followed routes and schedules. An extended online optimization framework is proposed, which automatically adapts to problem variations and enables the explicit consideration of up-to-date knowledge about the current performance of the controlled system. Actually, we use the mean punctuality observed in the transportation system to adjust the objective function utilized for solving the next decision problem instance. The search is guided toward least cost solutions coming along with high punctuality. We prove the applicability of this approach within comprehensive numerical experiments.     

Graphics in business decision making

Mountains of data can be converted into easily digested graphs so that decision makers can grasp the peaks and trends of economic situations and make rapid and confidential decisions. We will study how we can define simple models using a graphic-based Industrial Dynamics system (Forrester of MIT), then interact with them symbionically to obtain graphs of various manufacturing or sales considerations. We will proceed to apply graphic analysis techniques to these graphs in order to produce curves that identify the sensitivities of the analysis, to reinforce confidence in the decision to be made. Finally, we will discuss the progress and the potential of graphics in business decision making.     

Norms in artificial decision making

A method for forcing norms onto individual agents in a multi-agent system is presented. The agents under study are supersoft agents: autonomous artificial agents programmed to represent and evaluate vague and imprecise information. Agents are further assumed to act in accordance with advice obtained from a normative decision module, with which they can communicate. Norms act as global constraints on the evaluations performed in the decision module and hence no action that violates a norm will be suggested to any agent. Further constraints on action may then be added locally. The method strives to characterise real-time decision making in agents, in the presence of risk and uncertainty.     

Diagnosis and decision making in normative reasoning

Diagnosis theory reasons about incomplete knowledge and only considers the past. It distinguishes between violations and non-violations. Qualitative decision theory reasons about decision variables and considers the future. It distinguishes between fulfilled goals and unfulfilled goals. In this paper we formalize normative diagnoses and decisions in the special purpose formalism DIO(DE)² as well as in extensions of the preference-based deontic logic PDL. The DIagnostic and DEcision-theoretic framework for DEontic reasoning DIO(DE)² formalizes reasoning about violations and fulfillments, and is used to characterize the distinction between normative diagnosis theory and (qualitative) decision theory. The extension of the preference-based deontic logic PDL shows how normative diagnostic and decision-theoretic reasoning — i.e. reasoning about violations and fulfillments — can be formalized as an extension of deontic reasoning.     

Relating decision under uncertainty and multicriteria decision making models

This short overview paper points out the striking similarity between decision under uncertainty and multicriteria decision making problems, two areas which have been developed in an almost completely independent way until now. This pertains both to additive and non‐additive (including qualitative) approaches existing for the two decision paradigms. This leads to an emphasis on the remarkable formal equivalence between postulates underlying these approaches (like between the “sure‐thing principle” and mutual preferential independence of criteria). This analogy is exploited by surveying classical results as well as very recent advances. This unified view should be fruitful for a better understanding of the postulates underlying the approaches, for cross‐fertilization, and for adapting artificial intelligence uncertainty representation frameworks to preference modelling. © 2000 John Wiley & Sons, Inc.     

Privacy and rationality in individual decision making

Traditional theory suggests consumers should be able to manage their privacy. Yet, empirical and theoretical research suggests that consumers often lack enough information to make privacy-sensitive decisions and, even with sufficient information, are likely to trade off long-term privacy for short-term benefits     

Interaction effects of consumers' product class knowledge and agent search strategy on consumer decision making in electronic commerce

This paper investigates the interaction effects between the search strategy of software agents and consumers' product class knowledge in the context of consumers seeking to purchase cars on the Internet. The research design used was a 2/spl times/4, between-groups, completely randomized, two-factor, factorial design. The independent variables that were manipulated were product class knowledge (HIGH KNOWLEDGE, LOW KNOWLEDGE) and agent search strategy [elimination by aspects (EBA STRATEGY), weighted average method (WAD STRATEGY), profile building (PROFILE STRATEGY), simple hypertext (HYPERTEXT STRATEGY)]. The dependent variables that were measured were satisfaction with the decision process (SATISFACTION), confidence in the decision (CONFIDENCE), trust in the agent's recommendations (TRUST), propensity to purchase (PURCHASE), perceived cost savings (SAVINGS), and cognitive decision effort (EFFORT). Significant differences were found in the affective reactions of the subjects toward the agent/application depending on the level of product class knowledge possessed by the subjects. Subjects with high product class knowledge had more positive affective reactions toward agents/applications that used the WAD and EBA strategies as compared to the PROFILE strategy. Subjects with low product class knowledge had more positive affective reactions to agents/applications that used the PROFILE strategy as compared to the EBA and WAD strategies.     

Using hindsight in medical decision making

As the clinical picture of a patient evolves over time, more information becomes available. Certain procedure require time to perform, causing delay between the time when the tests are ordered and when the results are available. Furthermore, as the patient's condition changes over time, serial measurements can be made. The availability of more data allows a more accurate assessment of the patient. Uncertainties, guesses or errors that were made early in the clinical course of patient care can also be identified and resolved when more information is available. Reasoning with a stream of data that changes over time presents a challenge to the designers of expert systems. The use of hindsight in expert system requires that appropriate attention be paid to the temporal relations of the data and that care is exercised in revising decision. I present a data-dependency system, the Temporal Control Structure (TCS), designed to support reasoning with data changing over time and show how it can be used to implement reasoning by hindsight.     

Coordinated decision making in distributed applications

This paper describes how it is possible to use today's existing stateless PDPs such as the XACML PDP, to provide coordinated access control decision making throughout a distributed application. This is achieved by utilising an external database service to store the retained ADI that is needed by the PDPs. In this way the decision making can be coordinated and controlled throughout time and space. The retained ADI is modelled as coordination attributes of a coordination object, and coordination PIPs linked to each PDP access the coordination database service to retrieve the current values of the coordination attributes prior to the access control decision being made. Obligations in the access control policy define how the coordination attributes should be updated when the user is granted access to a resource. Three different modes of enforcing obligations are defined by a Chronicle directive, namely Chronicle = Before, Chronicle = After and Chronicle = With. The paper describes how the coordinated decision making has been implemented in Globus Toolkit v4, by developing a Coordinated PDP that incorporates a coordination PIP, an Obligations Service that implements the Chronicle = Before mode of operation, and a stateless PDP that makes the access control decisions; and an external coordination database grid service that has its own security controls to ensure that only Coordinated PDPs can access it. The paper concludes by discussing the implementation and indicating how the Chronicle = After and Chronicle = With modes of operation might also be supported in GT4.     

Two criteria in multiple decision making

The author obtains two solutions for the uncertainty problem in a multistep decision-making problem for a wide class of preference choice rules in a decision-making system. They are based on the principles of guaranteed and best results, respectively, with the criteria in the form of preferences on decisions defined by an explicitly specified utility function, which parametrically depends on a convex statistical regularity on the set of states and on the utility function on the consequences, which is determined to within a positive linear transformation.     

Consumer decision making in knowledge-based recommendation

In contrast to customers of bricks and mortar stores, users of online selling environments are not supported by human sales experts. In such situations recommender applications help to identify the products and/or services that fit the user’s wishes and needs. In order to successfully apply recommendation technologies we have to develop an in-depth understanding of decision strategies of users. These decision strategies are explained in different models of human decision making. In this paper we provide an overview of selected models and discuss their importance for recommender system development. Furthermore, we provide an outlook on future research issues.     

Reliability of decision making in human-organizations

In a human-organization system with n officers, a decision has to be made on whether to accept or to reject an innovation-oriented proposal that can either be good or bad. Each officer will review a given set of available information regarding the proposal in question and will thereafter return his or her decision. In the common formulation of this problem, the organization will accept the proposal if at least k officers decide for the project, where k is a prespecified threshold value. Hereby, each officer is subject to different errors and therefore, the final decision may be faulty as well. The reliability of such a system is the probability for the organization to make the right decision. In this paper, by imposing weights for each officer, generalized problem formulations are introduced and formulas for the corresponding reliability are derived     

On decision making and worth assessment

In this paper we present a tutorial review of the decision-making problem and of some of the tools available for treating it. We present a systems engineering framework developed by Hall and expanded by Warfield and Hill. Within that, framework we identify the decision-making and worth-assessment problems. As tools to effectively treat these problems, we present a summary review of the extensive form of decision analysis, modern utility theory, and the theory for evaluating preferences involving alternatives with multiple attributes. We also present a reasonably complete discussion of the worth-assessment procedure

With the above material as background, we examine the relationship between the worth-assessment procedure and decision analysis : and identify worth assessment as a particular form for evaluating multi-attributed preferences. In discussing worth assessment as a particular form for treating the multi-attribute problem, we point out some of the similarities and dissimilarities between the utility approach and the worth-assessment approach. By discussing worth assessment from this viewpoint and examining it in the light of modern utility theory, we prvoide some mathematical justification which has been lacking in the past and has opened the door for some criticism of worth assessment.     

Using metrics in management decision making

The amount of code in NASA systems has continued to grow over the past 30 years. This growth brings with it the increased risk of system failure caused by software. Thus, managing the risks inherent in software development and maintenance is becoming a highly visible and important field. The metrics effort within NASA's Mission Operations Directorate has helped managers and engineers better understand their processes and products. The toolkit helps ensure consistent data collection across projects and increases the number and types of analysis options available to project personnel. The decisions made on the basis of metrics analysis have helped project engineers make decisions about project and mission readiness by removing the inherent optimism of “engineering judgment”     

Analysis of decision making factors for equity investment by DEMATEL and Analytic Network Process

Existing methodologies of equity investment, such as fundamental analysis, technical analysis, and institutional investor analysis, explore important factors of stock price behaviors. However, the interdependent relationships of the key factors have not yet been fully studied. This paper provides the first analysis on the interactive relationships among the factors in incorporating the methods of Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). The empirical results show that factors from the existing analytical methodologies have significant interactive and self-feedback dynamics. Among the key factors, profitability is the most important one affecting investment decision, followed by growth and trading volume. In addition, due to the complexity of the ANP, this study proposes a new methodology to simplify the process, and empirical evidences indicate that the approach is effective and efficient.