Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

The evaluation of E-business related technologies in the Railway Industry

For the purposes of this paper, e-business is defined as: "the performance, automisation and organisation of transactions, or chains of them, and the gathering and publishing of data, electronically over a communication protocol" Little research has been conducted either into how e-business technology can be successfully evaluated, or into the associated costs and benefits specifically related to the transportation and railway industries. Based upon a review of the current literature and a series of interviews held with railway operators, track managers and transportation customers from the Australian Fortune 100, the paper puts forward a framework for the evaluation of e-business investments within the railway industry. The research reported here is aimed at developing a flexible interface that enables the decision maker to assess and evaluate a wide variety of complex interacting variables. The proposed approach uses a variety of evaluation methods, as opposed to searching for a single "best" approach. Additionally, an attempt is being made to include the complex interaction between the implementation of the new technology and the changing organisational setting. A model is proposed using fuzzy logic to handle incomplete and uncertain knowledge; as well as to combine criteria within a conceptual model from which "real-worth" evaluations can be performed. This model provides a systematic approach to guide the decision maker in the deployment of e-business and emerging technologies in the industry. After discussing the main findings from a literature review on the use of evaluation frameworks in IT related projects, the paper deals with the proposed framework in detail. The use of empirical data, which was obtained transportation customers to help define the main framework factors, is also discussed. Finally, the paper summarises the main implications for rail freight of customers’s perceptions and stated needs in the e-business domain

Evaluation of career readiness at an industrial technology program using a fuzzy approach

In this research, a quantitative model to measure the “career readiness” performance level of the current curriculum of the Industrial Technology and Packaging program at California Polytechnic State University is proposed. Career readiness is first defined through performance attributes and these attributes are further classified into specific categories and metrics. Using a fuzzy logic computational approach, “career readiness” measures are developed and a “career readiness” score referred to as (CRS) is calculated. The model is designed to be flexible, dynamic and easy to use. It should enable a systematic measurement of career readiness by producing a final integrated unit-less score. Results from the data collected for the Industrial Technology program’s main employers and graduates provided various insights about the level of career readiness the program currently provides in terms of strengths and weaknesses. In addition, these results, and the developed CRS approach, may serve as a practical tool for decision-making and improvement to various educational components to increase readiness level. Finally, the overall CRS, as well as its constituting scores, can be used to monitor progress along such improvements programs

A Fuzzy-Logic Approach to Dynamic Bayesian Severity Level Classification of Driver Distraction Using Image Recognition

open access articleDetecting and classifying driver distractions is crucial in the prevention of road accidents. These distractions impact both driver behavior and vehicle dynamics. Knowing the degree of driver distraction can aid in accident prevention techniques, including transitioning of control to a level 4 semi- autonomous vehicle, when a high distraction severity level is reached. Thus, enhancement of Advanced Driving Assistance Systems (ADAS) is a critical component in the safety of vehicle drivers and other road users. In this paper, a new methodology is introduced, using an expert knowledge rule system to predict the severity of distraction in a contiguous set of video frames using the Naturalistic Driving American University of Cairo (AUC) Distraction Dataset. A multi-class distraction system comprises the face orientation, drivers’ activities, hands and previous driver distraction, a severity classification model is developed as a discrete dynamic Bayesian (DDB). Furthermore, a Mamdani-based fuzzy system was implemented to detect multi- class of distractions into a severity level of safe, careless or dangerous driving. Thus, if a high level of severity is reached the semi-autonomous vehicle will take control. The result further shows that some instances of driver’s distraction may quickly transition from a careless to dangerous driving in a multi-class distraction context

Assessing the readiness to implement lean in healthcare institutions – a case study

We develop a lean readiness framework and an assessment methodology to quantify the readiness of healthcare institutions for implementing lean. We use stakeholder theory and work with a lean implementation team responsible for process improvement in a healthcare group to develop the framework. The framework uses fuzzy based input derived from the stakeholders of the healthcare institution to generate an overall ranking through ideal solution technique. The assessment method derives input from the readiness scores shared by various stakeholders. The ranking suggests future improvement areas to prepare the healthcare institution for a lean implementation project. We provide an alternative perspective of assessing the lean readiness of healthcare institutions before beginning a lean implementation project for both researchers and practitioners. Our research is the first to develop a lean readiness framework for healthcare institutions and demonstrate it using an assessment technique

Dynamic Model to Assess Organisational Readiness during Information System Implementation

This paper presents a methodology for assessing an organisation’s readiness to implement an information system (IS). We use the technique of fuzzy cognitive maps which draws on the theory of Neural Networks. The techniques comprising the model have been used in many applications, but their use in the planning of change management projects is relatively new. The paper explains the theory, presents a numerical example, and suggests practical uses of the model

Assessing the leanness of a supply chain using multi-grade fuzzy logic: a health-care case study

Purpose Numerous and diverse organizations have implemented lean principles and practices, which concentrate on improving the efficiency of business processes by reducing cost, waste, consumptions and effort. However, previous assessments have not focused on the leanness of the supply chain in a health-care setting. This paper aims to introduce a method for assessing the successful implementation of lean principles and tools in a supply chain. Furthermore, this paper validates the method in a health-care organization. Design/methodology/approach This paper starts with an extensive literature review on assessing leanness and using multi-grade fuzzy logic. Then, a conceptual model was developed to measure leanness. The conceptual model was validated by discussing the initial version with select academic experts, especially those who deal with leanness in health-care organizations. After responding to the experts’ valuable comments, the health-care organization that is the focus of this case study was chosen based on two criteria. The first criterion was the organization’s ability to participate in the study, and the second was the organization’s commitment to implementing lean principles. These criteria were important to ensure the organization had the necessary foundation for implementing change initiatives such as lean process improvements. Next, a multi-grade (multi-attributes) fuzzy logic was used for leanness measurement. A leanness index was calculated, and the results were validated using experts from the case study organization. Finally, the weaker areas of the organization’s processes were identified to point the way for further improvements. Findings The assessment indicated that the case study organization is not lean. The organization’s weaker attributes were identified, and improvements have been suggested. Research limitations/implications This study focused on a single health-care organization, which was selected from a limited pool of potential organizations, namely, organizations which are accredited by both the Saudi Central Board for Accreditation of Healthcare Institutions and the Joint Commission International. The scope of future research should be extended to multi-case studies to enhance the findings presented in this paper. This paper’s findings can be used to help decision-makers at health-care providers to implement lean thinking in supply chain processes. Practical implications This research may be interest to practicing supply chain managers, as it proposes what enablers, factors and attributes should be emphasized in lean implementation. The proposed model can work as an assessment tool to identify the gap between the present level of leanness and the desired leanness state so the health-care organization can identify what can be improved. This model enables decision-makers in hospital supply chain to take suitable actions for improving lean implementation level. Originality/value This study makes an original contribution to the body of research concerning lean principles; the study developed a conceptual model for leanness assessment that can be applied to the supply chain of health-care organizations. Indeed, the conceptual model is likely to be useful for assessing leanness outside of the health-care field, which suggests avenues for future research