A NEW LOGARITHM METHODOLOGY OF ADDITIVE WEIGHTS (LMAW) FOR MULTI-CRITERIA DECISION-MAKING: APPLICATION IN LOGISTICS

Logistics management has been playing a significant role in ensuring competitive growth of industries and nations. This study proposes a new Multi-Criteria Decision-making (MCDM) framework for evaluating operational efficiency of logistics service provider (LSP). We present a case study of comparative analysis of six leading LSPs in India using our proposed framework. We consider three operational metrics such as annual overhead expense (OE), annual fuel consumption (FC) and cost of delay (CoD, two qualitative indicators such as innovativeness (IN) which basically indicates process innovation and average customer rating (CR)and one outcome variable such as turnover (TO) as the criteria for comparative analysis. The result shows that the final ranking is a combined effect of all criteria. However, it is evident that IN largely influences the ranking. We carry out a comparative analysis of the results obtained from our proposed method with that derived by using existing established frameworks. We find that our method provides consistent results; it is more stable and does not suffer from rank reversal problem

Dynamics under Uncertainty: Modeling Simulation and Complexity

The dynamics of systems have proven to be very powerful tools in understanding the behavior of different natural phenomena throughout the last two centuries. However, the attributes of natural systems are observed to deviate from their classical states due to the effect of different types of uncertainties. Actually, randomness and impreciseness are the two major sources of uncertainties in natural systems. Randomness is modeled by different stochastic processes and impreciseness could be modeled by fuzzy sets, rough sets, Dempster–Shafer theory, etc

Evaluation of ERP Oracle Netsuite System for Purchasing Management Module at PT PQR using UTAUT2 Method

The purpose of the study was to evaluate the acceptance, use, and behavior of users towards the use of ERP Oracle NetSuite systems in the Purchasing Management module by analyzing how UTAUT2’s variables affected the user acceptances towards ERP Oracle NetSuite. The research method used is the UTAUT2 method, by conducting field studies to obtain information related to PT PQR and literature studies to support the theoretical data collection and analysis method to measure the user acceptance of ERP in the Oracle NetSuite Purchasing Management module system. In this study, 52 samples were collected using the saturated sample technique questionnaires. The data was analyzed using SEM-PLS with SmartPLS 3.0. The conclusion obtained from the results of this study is to focus more on improving performance expectancy, habit, and behavioral intention in using Oracle NetSuite ERP

Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

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Barriers to Information and Digital Technologies Adoption in Humanitarian Supply Chain Management : A Fuzzy AHP Approach

Peer reviewedPostprin

Conception et application d'une méthodologie multicritère floue de sélection de logiciels de planification et d'ordonnancement avancé (APS)

Avec la mondialisation, la croissance des entreprises et les besoins de plus en plus exigeants des clients, les défis en termes de planification et d’ordonnancement des opérations en environnement manufacturier ne cessent de croitre. Face à cette situation, les entreprises manufacturières sont dans l’obligation de mettre à jour leurs politiques de planification et d’ordonnancement en adoptant des systèmes et des approches de planifications nouvelles telles que la planification et l’ordonnancement avancés (POA). Dans cet exercice, les entreprises désirant implanter des approches de POA ont généralement deux possibilités. Elles peuvent choisir de développer une solution personnalisée ou alors d’implanter des logiciels commerciaux de POA. La deuxième piste est plus courue de nos jours. L’objectif de ce travail est d’accompagner les entreprises désirant améliorer la planification et l’ordonnancement de leurs opérations par la sélection et l’implantation d’un logiciel commercial de POA. Plus précisément, le but de ce travail est d’évaluer et de sélectionner parmi les logiciels commerciaux de POA disponibles sur le marché celui qui satisfait au mieux les besoins de l’entreprise. Trois sous objectifs ont été identifiés : la cartographie des processus de planification et d’ordonnancement de l’entreprise, la capture des besoins de l’entreprise et la conception d’une nouvelle méthodologie de sélection intégrant sous incertitude à la fois les besoins de l’entreprise et les critères et sous critères de sélection. La méthodologie adoptée pour cette étude est celle dictée par la science de la conception, qui permet l’itération du processus de conception afin de perfectionner et de valider les résultats ou les livrables obtenus. Des données sont recueillies auprès d’experts et des preneurs de décisions internes à l’entreprise à l’aide d’entrevues individuelles et de groupes. Par ailleurs, en guise de contributions de cette recherche, trois méthodes ont été conçues. La première méthode permet de cartographier les processus de l’entreprise. La deuxième méthode est destinée à la capture des besoins de l’entreprise tandis que la troisième méthode intègre le déploiement de la fonction qualité (DFQ), l’analyse hiérarchique des processus (AHP) et la méthode VIKOR pour la sélection du logiciel qui satisfait au mieux les besoins de l’entreprise. Cette intégration est rendue possible en mettant en place une version modifiée du DFQ. L’incertitude sur les données provenant des enquêtes adressées aux experts et aux preneurs de décision est considérée par l’utilisation de la logique floue et des variables linguistiques. L’approche globale de l’étude est appliquée à un cas réel d’entreprise manufacturière. Les résultats montrent la pertinence des méthodes développées face au problème de selection d’un logiciel de POA

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

A dual perspective towards building resilience in manufacturing organizations

Modern manufacturing organizations exist in the most complex and competitive environment the world has ever known. This environment consists of demanding customers, enabling, but resource intensive Industry 4.0 technology, dynamic regulations, geopolitical perturbations, and innovative, ever-expanding global competition. Successful manufacturing organizations must excel in this environment while facing emergent disruptions generated as biproducts of complex man-made and natural systems. The research presented in this thesis provides a novel two-sided approach to the creation of resilience in the modern manufacturing organization. First, the systems engineering method is demonstrated as the qualitative framework for building literature-derived organizational resilience factors into organizational structures under a life cycle perspective. A quantitative analysis of industry expert survey data through graph theory and matrix approach is presented second to prioritize resilience factors for strategic practical implementation