Papers by Ayeley Tchangani
Advances in intelligent systems and computing, Aug 18, 2017
The aim of this paper is to formulate a quantitative integrated model of how quality and producti... more The aim of this paper is to formulate a quantitative integrated model of how quality and productivity performances of a production system are interrelated. Indeed, productivity and quality, some of most important objectives of a production system have been studied separately since decades whereas studies are demonstrating a close interaction between them nowadays. Such an integrated model will be beneficial to engineers during design and/or operation stages of the system because it can be used to set up or to assess overall performance measures such as: total production rate, effective production rate, machines availability, inspection policies performance, etc. Dynamic Bayesian network will be used as the underlying mathematical tool to describe the dynamics of the state of the system as they are well suited for the representation of stochastic processes (machine failures, quality failures, etc.).
HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific re... more HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.
HAL (Le Centre pour la Communication Scientifique Directe), 2009
IFAC-PapersOnLine, Jul 1, 2017
Proceedings Of The Institution Of Mechanical Engineers, Part O: Journal Of Risk And Reliability, Aug 1, 2018
HAL (Le Centre pour la Communication Scientifique Directe), 2009
International audienc
Managing risks for large-scale complex systems requires identifying, assessing, and prioritizing ... more Managing risks for large-scale complex systems requires identifying, assessing, and prioritizing different risk scenarios or undesirable events that systems may face; coping with risks when engaged in some activities or decision making processes such as deciding to invest in a company or a country, to offer loans to applicants, to recruit a candidate to fill vacant position, to fund projects or infrastructures, etc. necessitate to categorize the targeted entities. Prioritizing or filtering risks (undesirable events or events scenarios) or categorizing risky entities for some activities return to assigning them to a predefined classes or categories for their appropriate treatment. On other hand a scenario or an entity as well as a class or category will be characterized by some attributes that represent basically its impact or constraints on different objectives, issues, stakes, or consequences that do represent some interests for decision makers and/or stakeholders. This is a nominal classification problem that is a subfield of multi-criteria decision making problems in general. As the attributes and/or features characterizing classes may not be defined precisely, a fuzzy representation can be used to treat this uncertainty leading to what is known as fuzzy nominal classification. If one was to classify using only one feature there will be some values of that feature that leads to certain choice or certain rejection of a particulate class and those for which some hesitation or doubt will exist leading to some bipolarity. In this communication, a bipolar fuzzy nominal classification framework will be built to address risks filtering and/or categorization issues; a real world application in the domain of countries' risk classification show the potentiality of the derived approach.
International Journal of Management and Decision Making, 2023
HAL (Le Centre pour la Communication Scientifique Directe), Feb 1, 2009
OATAO is an open access repository that collects the work of some Toulouse researchers and makes ... more OATAO is an open access repository that collects the work of some Toulouse researchers and makes it freely available over the web where possible.
Advances in computational intelligence and robotics book series, 2014
Decision analysis, the mechanism by which a final decision is reached in terms of choice (choosin... more Decision analysis, the mechanism by which a final decision is reached in terms of choice (choosing an alternative or a subset of alternatives from a large set of alternatives), ranking (ranking alternatives of a set from the worst to the best), classification (assigning alternatives to some known classes or categories), or sorting (clustering alternatives to form homogeneous classes or categories) is certainly the most pervasive human activity. Some decisions are made routinely and do not need sophisticated algorithms to support decision analysis process whereas other decisions need more or less complex processes to reach a final decision. Methods and models developed to solve decision analysis problems are in constant evolution going from mechanist models of operational research to more sophisticated and soft computing-oriented models that attempt to integrate human attitude (emotion, affect, fear, egoism, altruism, selfishness, etc.). This complex, soft computing and near human mechanism of problem solving is rendered possible thanks to the overwhelming computational power and data storage possibility of modern computers. The purpose of this chapter is to present new and recent developments in decision analysis that attempt to integrate human judgment through bipolarity notion.
IGI Global eBooks, 2018
A collective choice problem is a decision problem where a certain number (possibly reduced to one... more A collective choice problem is a decision problem where a certain number (possibly reduced to one) of agents, stakeholders, or decision makers must select alternative(s) from a possibly large set or universe of alternatives in order to satisfy some collective as well as individual objectives. The purpose of this chapter is to consider the modeling process of collective choice problem when coping with human attitude in terms of social influence, indecision, uncertainty, etc. Using bipolar analysis that consist in evaluating alternatives by two opposite measures (a measure taking into account positive aspect of the alternative and that resuming its negative aspects) at individual level as well as community level permit to some extent embedding human attitudes in the decision process.
Engineering Applications of Artificial Intelligence, 2011
Continuous improvement in industrial processes is increasingly a key element of competitiveness f... more Continuous improvement in industrial processes is increasingly a key element of competitiveness for industrial systems. The management of experience feedback in this framework is designed to build, analyze and facilitate the knowledge sharing among problem solving practitioners of an organization in order to improve processes and products achievement. During Problem Solving Processes, the intellectual investment of experts is often considerable and the opportunities for expert knowledge exploitation are numerous: decision making, problem solving under uncertainty, and expert configuration. In this paper, our contribution relates to the structuring of a cognitive experience feedback framework, which allows a flexible exploitation of expert knowledge during Problem Solving Processes and a reuse such collected experience. To that purpose, the proposed approach uses the general principles of root cause analysis for identifying the root causes of problems or events, the conceptual graphs formalism for the semantic conceptualization of the domain vocabulary and the Transferable Belief Model for the fusion of information from different sources. The underlying formal reasoning mechanisms (logic-based semantics) in conceptual graphs enable intelligent information retrieval for the effective exploitation of lessons learned from past projects. An example will illustrate the application of the proposed approach of experience feedback processes formalization in the transport industry sector.
The aim of this paper is to formulate a quantitative integrated model of how quality and producti... more The aim of this paper is to formulate a quantitative integrated model of how quality and productivity performances of a production system are interrelated. Indeed, productivity and quality, some of most important objectives of a production system have been studied separately since decades whereas studies are demonstrating a close interaction between them nowadays. Such an integrated model will be beneficial to engineers during design and/or operation stages of the system because it can be used to set up or to assess overall performance measures such as: total production rate, effective production rate, machines availability, inspection policies performance, etc. Dynamic Bayesian network will be used as the underlying mathematical tool to describe the dynamics of the state of the system as they are well suited for the representation of stochastic processes (machine failures, quality failures, etc.).
HAL (Le Centre pour la Communication Scientifique Directe), Mar 31, 2008
CRC Press eBooks, Jul 13, 2022
2020 International Conference on Decision Aid Sciences and Application (DASA), 2020
Decision-making is certainly the most widespread of all human activities, whether individual or b... more Decision-making is certainly the most widespread of all human activities, whether individual or by a group. Some decisions, especially individual decisions, are easy to make and do not require sophisticated algorithms to arrive at a solution. Others, on the other hand, and especially in the case of group decision-making, require the establishment of frameworks, rules or algorithms of varying degrees of sophistication to arrive at a satisfactory solution. In this process, the most difficult part is certainly the modeling and treatment of the relationships between the actors in the decision-making group. The objective of this paper is therefore to build a framework for modeling and analyzing interactions between decision-makers in a group on computational bases in the sense that these interactions will be characterized by numerical parameters. The constant concern in this work is to get as close as possible to human behavior by using bipolar analysis.
Advances in Public Policy and Administration, 2019
A collective choice problem is a decision problem where a certain number (possibly reduced to one... more A collective choice problem is a decision problem where a certain number (possibly reduced to one) of agents, stakeholders, or decision makers must select alternative(s) from a possibly large set or universe of alternatives in order to satisfy some collective as well as individual objectives. The purpose of this chapter is to consider the modeling process of collective choice problem when coping with human attitude in terms of social influence, indecision, uncertainty, etc. Using bipolar analysis that consist in evaluating alternatives by two opposite measures (a measure taking into account positive aspect of the alternative and that resuming its negative aspects) at individual level as well as community level permit to some extent embedding human attitudes in the decision process.
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Papers by Ayeley Tchangani