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Article
Publication date: 12 February 2018

Fei Du and Feiyan Liu

This study aims to propose a new decision-making method by integrating case-based decision theory and the Dempster–Shafer theory of evidence.

Abstract

Purpose

This study aims to propose a new decision-making method by integrating case-based decision theory and the Dempster–Shafer theory of evidence.

Design/methodology/approach

The study developed the entire computational procedures for the proposed method and used a numerical example to illustrate its method.

Findings

The results show that not only the own experiences of the decision-maker but also the opinions of other persons contribute to the selection. Case-based decision theory provides a fundamental technique for the decision-making procedure, and the Dempster–Shafer theory of evidence offers support to deal with the different sources of decision information.

Research limitations/implications

In case-based decision theory, the utility is a subjective concept, which cannot be measured easily in numbers. Thus, future research should seek a new method to replace the utility. In addition, how to assess the importance of different persons’ experiences and opinions is an important component of this method.

Originality/value

The contributions of the paper are mainly reflected in three aspects. The first is to expand the traditional concept of “case” of case-based decision theory to multiple sources of cases, which include not only the decision-maker’s own experiences but also other persons’ opinions. The second is to provide a decision-making framework by integrating case-based decision theory and the Dempster–Shafer theory of evidence. The third is to develop the entire computational procedures for the proposed method.

Details

Journal of Modelling in Management, vol. 13 no. 1
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 8 February 2022

Arezou Asgharnezhad and Soroush Avakh Darestani

To outsource part of their work, organizations are looking for suppliers who also have green criteria with other criteria. Selecting suppliers begins with the definition of…

Abstract

Purpose

To outsource part of their work, organizations are looking for suppliers who also have green criteria with other criteria. Selecting suppliers begins with the definition of potential suppliers and then selects the best among them. This study aims to present a two-part approach for selecting suppliers consisting of suppliers’ prioritization.

Design/methodology/approach

In the first part, the criteria that influence on selecting the suppliers have been identified and extracted using the literature review and experts’ opinion which consists of 19 criteria. Then, these criteria were evaluated by the content validity ratio index and using experts’ opinions, and finally, 16 criteria were selected for selecting green suppliers in a polyethylene’s products producer company in Iran. In the next step, suppliers are selected in a green supply chain using multi-criteria decision-making methods such as Dempster–Shafer theory and grey relationship analysis, which is a strategic decision.

Findings

This study attempts to improve the level of reliance on the whole uncertain degree by combining Dempster–Shafer theory and grey relational analysis (GRA), which makes the grey analysis method more robust and its results more reliable. The findings show that Supplier 4 is ranked as first within six suppliers.

Originality/value

Using GRA and Dempster–Shafer theory for green supplier selection problem in polyethylene industry is the novelty of this work.

Details

Management Research Review, vol. 45 no. 12
Type: Research Article
ISSN: 2040-8269

Keywords

Book part
Publication date: 14 July 2006

Mohamed E. Bayou and Thomas Jeffries

The absence of the reasoning stage in the analysis of long-term investment decision creates a serious gap in this classic topic in management accounting literature. The purpose of…

Abstract

The absence of the reasoning stage in the analysis of long-term investment decision creates a serious gap in this classic topic in management accounting literature. The purpose of this paper is to fill this gap. The traditional analysis focuses on the evaluation stage using capital budgeting tools to rank alternative investment proposals. It tacitly assumes that the decision is to be made, thereby bypassing the reasoning stage. However, the reasoning stage may reveal that there is no sufficient justification (reasoning) to consider searching for and evaluating alternative proposals for this decision. Focusing on the reasoning component, the paper combines Fritz's (1989, 1990) “creative tension” and Janis and Mann's (1977) “challenges” as the driving forces for the problem-finding step. To demonstrate the significance of filling the reasoning gap in the long-term investment decision, the paper selects the modular manufacturing system and the complex investment decision required for its adoption. Using hypothetical data, the paper employs the Dempster-Shafer Theory of Evidence and Omer, et al's (1995) algorithm to compute the belief and plausibility values of the three reasoned actions: (1) maintain the status quo, (2) adopt Level 2 (assembly) modularity or (3) adopt Level 2 (design) modularity.

The contributions of the paper include (1) highlighting a critical gap currently existing in one of the classical decisions in the management accounting literature; (2) developing a framework for filling this gap and (3) applying this framework to the intricate nature of the modular manufacturing system and its complex investment decision.

Details

Advances in Management Accounting
Type: Book
ISBN: 978-1-84950-447-8

Article
Publication date: 1 August 2004

D. Dutta Majumder and Kausik Kumar Majumdar

In this paper, we present a brief study on various paradigms to tackle complexity or in other words manage uncertainty in the context of understanding science, society and nature…

1083

Abstract

In this paper, we present a brief study on various paradigms to tackle complexity or in other words manage uncertainty in the context of understanding science, society and nature. Fuzzy real numbers, fuzzy logic, possibility theory, probability theory, Dempster‐Shafer theory, artificial neural nets, neuro‐fuzzy, fractals and multifractals, etc. are some of the paradigms to help us to understand complex systems. We present a very detailed discussion on the mathematical theory of fuzzy dynamical system (FDS), which is the most fundamental theory from the point of view of evolution of any fuzzy system. We have made considerable extension of FDS in this paper, which has great practical value in studying some of the very complex systems in society and nature. The theories of fuzzy controllers, fuzzy pattern recognition and fuzzy computer vision are but some of the most prominent subclasses of FDS. We enunciate the concept of fuzzy differential inclusion (not equation) and fuzzy attractor. We attempt to present this theoretical framework to give an interpretation of cyclogenesis in atmospheric cybernetics as a case study. We also have presented a Dempster‐Shafer's evidence theoretic analysis and a classical probability theoretic analysis (from general system theoretic outlook) of carcinogenesis as other interesting case studies of bio‐cybernetics.

Details

Kybernetes, vol. 33 no. 7
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 1 October 1996

George J. Klir and David Harmanec

Provides an overview of major developments pertaining to generalized information theory during the lifetime of Kybernetes. Generalized information theory is viewed as a collection…

570

Abstract

Provides an overview of major developments pertaining to generalized information theory during the lifetime of Kybernetes. Generalized information theory is viewed as a collection of concepts, theorems, principles, and methods for dealing with problems involving uncertainty‐based information that are beyond the narrow scope of classical information theory. Introduces well‐justified measures of uncertainty in fuzzy set theory, possibility theory, and Dempster‐Shafer theory. Shows how these measures are connected with the classical Hartley measure and Shannon entropy. Discusses basic issues regarding some principles of generalized uncertainty‐based information.

Details

Kybernetes, vol. 25 no. 7/8
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 1 July 1997

F. McErlean, D.A. Bell, A. Barr and G. Mulvenna

The management of uncertainty has received much attention recently in the fields of database and artificial intelligence. Several methods of evidential reasoning have been…

Abstract

The management of uncertainty has received much attention recently in the fields of database and artificial intelligence. Several methods of evidential reasoning have been proposed for real‐world problems with which uncertainty is associated. Considers one of these problems, that of classification, which is encountered in many domains including medicine. Focuses on a classification technique for knowledge discovery (KD). Reasoning about classifications is a primary interest in KD. Deals with obtaining evidence to confirm or refute classes. Searches for any data dependencies which exist between a classifier attribute and any of the property attributes. To illustrate the method compares a neural network classification with one based on Tanimoto’s method. It is important to note that the aim is to demonstrate this approach rather than to compare these two methods of classification. After extracting the data dependency information, employs a non‐numeric evidential reasoning method to see how well this evidence supports each of the two respective classifications.

Details

Kybernetes, vol. 26 no. 5
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 4 August 2014

Daniel W.M. Chan, Joseph H.L. Chan and Tony Ma

This paper aims to develop a fuzzy risk assessment model for construction projects procured with target cost contracts and guaranteed maximum price contracts (TCC/GMP) using the…

Abstract

Purpose

This paper aims to develop a fuzzy risk assessment model for construction projects procured with target cost contracts and guaranteed maximum price contracts (TCC/GMP) using the fuzzy synthetic evaluation method, based on an empirical questionnaire survey with relevant industrial practitioners in South Australia.

Design/methodology/approach

A total of 34 major risk factors inherent with TCC/GMP contracts were identified through an extensive literature review and a series of structured interviews. A questionnaire survey was then launched to solicit the opinions of industrial practitioners on risk assessment of such risk factors.

Findings

The most important 14 key risk factors after the computation of normalised values were selected for undertaking fuzzy evaluation analysis. Five key risk groups (KRGs) were then generated in descending order of importance as: physical risks, lack of experience of contracting parties throughout TCC/GMP procurement process, design risks, contractual risks and delayed payment on contracts. These survey findings also revealed that physical risks may be the major hurdle to the success of TCC/GMP projects in South Australia.

Practical implications

Although the fuzzy risk assessment model was developed for those new-build construction projects procured by TCC/GMP contracts in this paper, the same research methodology may be applied to other contracts within the wide spectrum of facilities management or building maintenance services under the target cost-based model. Therefore, the contribution from this paper could be extended to the discipline of facilities management as well.

Originality/value

An overall risk index associated with TCC/GMP construction projects and the risk indices of individual KRGs can be generated from the model for reference. An objective and a holistic assessment can be achieved. The model has provided a solid platform to measure, evaluate and reduce the risk levels of TCC/GMP projects based on objective evidence instead of subjective judgements. The research methodology could be replicated in other countries or regions to produce similar models for international comparisons, and the assessment of risk levels for different types of TCC/GMP projects (including new-build or maintenance) worldwide.

Article
Publication date: 1 November 1997

F. McErlean and D.A. Bell

The management of uncertainty has received much attention recently in the fields of database and artificial intelligence. Several methods of evidential reasoning have been…

Abstract

The management of uncertainty has received much attention recently in the fields of database and artificial intelligence. Several methods of evidential reasoning have been proposed for real‐world problems with which uncertainty is associated. One of these problems is that of classification and it is encountered in many domains including medicine, which is considered here. Focuses on a classification technique for knowledge discovery (KD). Reasoning about classifications is a primary interest in KD. Obtains evidence to confirm or refute classes by searching for any data dependencies which exist between a classifier attribute and any of the property attributes. To illustrate the method, compares a neural network classification with one based on Tanimoto’s method. The aim was to demonstrate the approach rather than to compare the two methods of classification. After extracting the data dependency information, employs a non‐numeric evidential reasoning method to see how well this evidence supports each of the two respective classifications.

Details

Kybernetes, vol. 26 no. 8
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 29 July 2014

Hou Liqiang, Cai Yuanli, Zhang Rongzhi, Li Hengnian and Li Jisheng

A multi-disciplinary robust design optimization method for micro Mars entry probe (no more than 0.8 m in diameter) is proposed. The purpose of this paper is to design a Mars entry…

Abstract

Purpose

A multi-disciplinary robust design optimization method for micro Mars entry probe (no more than 0.8 m in diameter) is proposed. The purpose of this paper is to design a Mars entry probe, not only the geometric configuration, but the trajectory and thermal protection system (TPS). In the design optimization, the uncertainties of atmospheric and aerodynamic parameters are taken into account. The probability distribution information of the uncertainties are supposed to be unknown in the design. To ensure accuracy levels, time-consuming numerical models are coupled in the optimization. Multi-fidelity approach is designed for model management to balance the computational cost and accuracy.

Design/methodology/approach

Uncertainties which cannot defined by usual Gaussian probability distribution are modeled with degree of belief, and optimized through with multiple-objective optimization method. The optimization objectives are set to be the thermal performance of the probe TPS and the corresponding belief values. Robust Pareto front is obtained by an improved multi-objective density estimator algorithm. Multi-fidelity management is performed with an Artificial Neural Network (ANN) surrogate model. Analytical model is used first, and then with the improvement of accuracy, rather complex numerical models are activated. ANN updates the database during the optimization, and makes the solutions finally converge to a high-level accuracy.

Findings

The optimization method provides a way for conducting complex design optimization involving multi-discipline and multi-fidelity models. Uncertainty effects are analyzed and optimized through multi-disciplinary robust design. Because of the micro size, and uncertain impacts of aerodynamic and atmospheric parameters, simulation results show the performance trade-off by the uncertainties. Therefore an effective robust design is necessary for micro entry probe, particularly when details of model parameter are not available.

Originality/value

The optimization is performed through a new developed multi-objective density estimator algorithm. Affinity propagation algorithm partitions adaptively the samples by passing and analyzing messages between data points. Local principle component techniques are employed to resample and reproduce new individuals in each cluster. A strategy similar to NSGA-II selects data with better performance, and converges to the Pareto front. Models with different fidelity levels are incorporated in the multi-disciplinary design via ANN surrogate model. Database of aerodynamic coefficients is updated in an online manner. The computational time is greatly reduced while keeping nearly the same accuracy level of high fidelity model.

Details

Engineering Computations, vol. 31 no. 6
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 26 June 2009

Bo Chen, Jifeng Wang and Shanben Chen

Welding process is a complicated process influenced by many interference factors, a single sensor cannot get information describing welding process roundly. This paper…

Abstract

Purpose

Welding process is a complicated process influenced by many interference factors, a single sensor cannot get information describing welding process roundly. This paper simultaneously uses different sensors to get different information about the welding process, and uses multi‐sensor information fusion technology to fuse the different information. By using multi‐sensors, this paper aims to describe the welding process more precisely.

Design/methodology/approach

Electronic and welding pool image information are, respectively, obtained by arc sensor and image sensor, then electronic signal processing and image processing algorithms are used to extract the features of the signals, the features are then fused by neural network to predict the backside width of weld pool.

Findings

Comparative experiments show that the multi‐sensor fusion technology can predict the weld pool backside width more precisely.

Originality/value

The multi‐sensor fusion technology is used to fuse the different information obtained by different sensors in a gas tungsten arc welding process. This method gives a new approach to obtaining information and describing the welding process.

Details

Sensor Review, vol. 29 no. 3
Type: Research Article
ISSN: 0260-2288

Keywords

1 – 10 of 210