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

İMALAT İSÇİLERİNİN SEÇİM KRİTERLERİNİN BULANIK AHS YÖNTEMİ İLE ANALİZİ

An analytical way to reach the best decision is more preferable in many business platforms. When variables are quantitative and number of criteria is not high, then one can use several analysis tools and make his/her decision and solve the problem. However, many times beside the measurable variables, there exist qualitative variables for decision making problems, or people are supposed to prefer the best among the many choices. Even if only linguistic evaluations may be available for such problems, an analytical way to find the solution systematically to make a successful decision is needed. Fuzzy Analytical Hierarchy Process (Fuzzy AHP) is one of the best ways for deciding among the complex criteria structure in different levels. Fuzzy AHP is a synthetic extension of classical AHP method when the fuzziness of the decision makers is considered. In this paper, the criteria set and their importance for the selection of manufacturing employee in a firm producing shoe machines are analyzed. Finally a systematic solution and decision support are provided for management. Birçok is ortamında analitik yöntemler, en iyi kararı vermek adına daha çok tercih görmektedir. Sayısal olarak ölçülebilen degiskenlerin ve kriterlerin varlıgında kullanılabilecek birçok analiz ve problem çözme teknigi bulunabilirken, kalitatif degiskenlerle seçim ya da karar verme zorunlulugu oldugunda farklı yaklasımlara gerek duyulmaktadır. Böyle bir durumda, öznel ve sözel degerlendirmeler yapma zorunlugu dogmakla birlikte, sistematik ve analitik bir yol izlemek basarılı karar vermek açısından kaçınılmazdır. Bu kosularda özellikle karar verme ortamı bulanık veriler içeriyorsa, en çok tercih edilen tekniklerden biri de Bulanık Analitik Hiyerarsi Süreci (Bulanık AHS)dir. Karmasık kriter set ve çoklu düzey yapısında seçenekler içerisinde en iyi seçimi yapma konusunda basarılı kararlar alınmasında sık kullanıma sahiptir. Bulanık AHS karar vericilerin yaptıkları yorum ve degerlendirmelerde belli bir bulanıklık oldugu düsünüldügünde ortaya çıkan ve AHS'nin bir uzantısı olarak gelistirilen sentetik bir yaklasımdır. Bu çalısmada, ayakkabı makinalar üreten bir firma için imalatta çalısacak isçilerin seçiminde hangi kriterlerin gözetildigi ve bu kriterlerin hangi agırlıklarla kararda etkili oldugu bulanık AHS yöntemi ile analiz edilmis, firma yetkilerine sistematik bir çözüm ve karar destegi saglanmıstır

Review of Health Prognostics and Condition Monitoring of Electronic Components

To meet the specifications of low cost, highly reliable electronic devices, fault diagnosis techniques play an essential role. It is vital to find flaws at an early stage in design, components, material, or manufacturing during the initial phase. This review paper attempts to summarize past development and recent advances in the areas about green manufacturing, maintenance, remaining useful life (RUL) prediction, and like. The current state of the art in reliability research for electronic components, mainly includes failure mechanisms, condition monitoring, and residual lifetime evaluation is explored. A critical analysis of reliability studies to identify their relative merits and usefulness of the outcome of these studies' vis-a-vis green manufacturing is presented. The wide array of statistical, empirical, and intelligent tools and techniques used in the literature are then identified and mapped. Finally, the findings are summarized, and the central research gap is highlighted

Dynamic vehicle routing problems: Three decades and counting

Since the late 70s, much research activity has taken place on the class of dynamic vehicle routing problems (DVRP), with the time period after year 2000 witnessing a real explosion in related papers. Our paper sheds more light into work in this area over more than 3 decades by developing a taxonomy of DVRP papers according to 11 criteria. These are (1) type of problem, (2) logistical context, (3) transportation mode, (4) objective function, (5) fleet size, (6) time constraints, (7) vehicle capacity constraints, (8) the ability to reject customers, (9) the nature of the dynamic element, (10) the nature of the stochasticity (if any), and (11) the solution method. We comment on technological vis-à-vis methodological advances for this class of problems and suggest directions for further research. The latter include alternative objective functions, vehicle speed as decision variable, more explicit linkages of methodology to technological advances and analysis of worst case or average case performance of heuristics.© 2015 Wiley Periodicals, Inc

Supplier evaluation and selection in fuzzy environments: a review of MADM approaches

In past years, the multi-attribute decision-making (MADM) approaches have been extensively applied by researchers to the supplier evaluation and selection problem. Many of these studies were performed in an uncertain environment described by fuzzy sets. This study provides a review of applications of MADM approaches for evaluation and selection of suppliers in a fuzzy environment. To this aim, a total of 339 publications were examined, including papers in peer-reviewed journals and reputable conferences and also some book chapters over the period of 2001 to 2016. These publications were extracted from many online databases and classified in some categories and subcategories according to the MADM approaches, and then they were analysed based on the frequency of approaches, number of citations, year of publication, country of origin and publishing journals. The results of this study show that the AHP and TOPSIS methods are the most popular approaches. Moreover, China and Taiwan are the top countries in terms of number of publications and number of citations, respectively. The top three journals with highest number of publications were: Expert Systems with Applications, International Journal of Production Research and The International Journal of Advanced Manufacturing Technology

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

The creation of “Questions Bank" and introduction of 2.0. examination session

In the Institute of American Studies and Polish Diaspora Jagiellonian University, with the support of the Distance Learning Centre at the Jagiellonian University was introduced an innovative method of examination based on empowering the students. During the 2014 session, the students were invited to create test questions. Accepted by the lecturer questions were used on he exam. Extensive “Questions Bank” may be used in subsequent examinations 2.0. The authors of the paper present practical advice on how to prepare and carry out such an examination. They share know how of practical suggestions from pedagogical to technical aspect of moving from teaching to learning while using the idea of Questions Bank. They discuss the impact on the motivation and creativity of students, the principles of achievement and assessment, methods of verifying the content of the questions and technical measures to make questions and hindering cheating. The use of innovative methods of preparing and conducting the exam based on the Questions Bank had a positive impact on the mobilization and involvement of students, which resulted in a very good performance evaluation questionnaires of the lecture