Analytic Hierarchy Process and Supply Chain Management: A Bibliometric Study

AbstractA comparative study was used to outline the literature in the research topic. This paper aims to present a bibliometric study ofmulti-criteria decision-making methods most applied in publications from 1990 to 2014. Our research presented relations of papers published in the Web of Science Core Collection, regarding the following keywordsAnalytic Hierarchy Process and Supply Chain. The research evidenced that the Analytic Hierarchy Process has been the method mostapplied in publications from 1993. It also showed the analysis of the predecessor and successor citation network for the selected publications under topics as supplier selection, supply development, performance measurement and value chain through the CitNetExplore software

Enhancing the competitiveness of manufacturers through Small-scale Intelligent Manufacturing System (SIMS): A supply chain perspective

An electronic version of the final, peer-reviewed manuscript upon acceptance for publication made publicly after an IEEE embargo period of 24 months from the date of publication. Link to publishers version:http://doi.org/10.1109/ICITM.2017.7917904In order to survive in this competitive and ever changing market, manufacturers have to improve and enhance the competitiveness, flexibility, responsiveness and sustainability with the application of the cutting-edge technologies and innovative management methods. New concepts, i.e., Intelligent manufacturing, flexible manufacturing, agile manufacturing, network manufacturing, green manufacturing and Industry 4.0, etc., have been proposed and developed in recent years based upon the newest and most advanced manufacturing technologies and Information and Communication technologies (ICT). This paper presents a new concept: Small-scale Intelligent Manufacturing System (SIMS), and the comparison with previous concepts and the benefits of SIMS are discussed in this paper. Different from the previous research works which mainly emphasize the technological integration for improving the flexibility and intelligence of an individual manufacturing system, this paper, however, focuses on and discusses the supply chain problems arisen from a holistic perspective. The features of the supply chain for realizing small-scale intelligent production and responsive distribution are discussed, and the limitation and future works are also discussed and suggested latter in this paper

Sustainable Warehouse Location Selection in Humanitarian Supply Chain: Multi-Criteria Decision-Making Approach

The frequency of catastrophic natural disasters is rising, and much emphasis is being given to the Humanitarian Supply chain (HSC). The main goal of relief efforts is to get enough emergency supplies to the area hit by the disaster as quickly as possible. The decision of where to locate warehouses that will store relief supplies presents a significant obstacle for humanitarian relief organizations as they work to enhance their capacity for providing aid and their rescue plan. A non-optimal location could make the search and rescue efforts harder. More importantly, it has been seen that when these kinds of geographical sites are evaluated, social and environmental issues are not considered. This research paper aims to make humanitarian networks more accountable by determining the ideal warehouse site and considering both traditional and sustainable factors. A framework for selecting warehouses to keep relief goods was devised using the Multi-Criteria Decision Making (MCDM) approach. Best-Worst and TOPSIS (“Technique for Order Performance by Similarity to the Ideal Solution”) methods were used to rank the potential locations based on Cost, Logistics, Environmental, and Social Criteria. A research study has been done in the State of West Bengal (District Arambagh)

A Methodology For Minimizing The Oscillations In Supply Chains Using System Dynamics And Genetic Algorithms

Supply Chain Management (SCM) is a critically significant strategy that enterprises depend on to meet challenges that they face because of highly competitive and dynamic business environments of today. Supply chain management involves the entire network of processes from procurement of raw materials/services/technologies to manufacturing or servicing intermediate products/services to converting them into final products or services and then distributing and retailing them till they reach final customers. A supply chain network by nature is a large and complex, engineering and management system. Oscillations occurring in a supply chain because of internal and/or external influences and measures to be taken to mitigate/minimize those oscillations are a core concern in managing the supply chain and driving an organization towards a competitive advantage. The objective of this thesis is to develop a methodology to minimize the oscillations occurring in a supply chain by making use of the techniques of System Dynamics (SD) and Genetic Algorithms (GAs). System dynamics is a very efficient tool to model large and complex systems in order to understand their complex, non-linear dynamic behavior. GAs are stochastic search algorithms, based on the mechanics of natural selection and natural genetics, used to search complex and non-linear search spaces where traditional techniques may be unsuitable

A multi-criterion genetic algorithm for order distribution in a demand driven supply chain

This paper develops a multi-criterion genetic optimization procedure, specifically designed for solving optimization problems in supply chain management. The proposed algorithm is discussed with an order distribution problem in a demand driven supply chain network. It combines the analytic hierarchy process (AHP) with genetic algorithms. AHP is utilized to evaluate the fitness values of chromosomes. The proposed algorithm allows decision-makers to give weighting for criteria using a pair-wise comparison approach. The numerical results obtained from the proposed algorithm are compared with the one obtained from the multi-objective mixed integer programming approach. The comparison shows that the proposed algorithm is reliable and robust. In addition, it provides more control and information for the decision-makers to gain a better insight of the supply chain network.link_to_subscribed_fulltex

How to Make the Most Productive Intervention in a Complex Economic System

Information about supply and demand propagates through supply chains in a queueing network with people and computers as batch information processors. As each batch processor delays propagation of information whilst pursuing optimal local decisions, the effect is delay and distortion of the information that is used to commit resources to actions in the supply chain. This thesis investigates the effect of delay and imperfect information as a source of error, to establish the case for change in research focus from optimal exploitation of physical constraints to optimal exploitation of information. In the context of real world supply chains, the thesis asks "How does one make the most productive intervention in a complex economic system?" and pursues a meta-intervention which perpetually minimises the discovered error-term. Evidence from literature indicates that agent-based modelling permits real-time peer-to-peer communication and distributed optimisation. Based on the literature the research project designs and develops an agent-based model which operates in real-time without batch-processes and can perform incremental multi-objective optimisation under realistic (chronologically progressive) conditions for decision making. The agent based model is then used to investigate two real-world supply chains, as case studies, which reveals a significant improvement of profitability and order-fulfilment. The thesis concludes that agent-based modelling is a very promising direction for "making the most productive intervention" as it reduces delay to a minimum. Finally it recommends that continuous improvement of decision making methods is a role better suited for humans, rather than operational decision making where computers cope much better with the high amount of detailed information

Métodos para la comparación de alternativas mediante un Sistema de Ayuda a la Decisión SAD y “Soft Computing"

[SPA] El proceso de resolución de problemas que supone la acción de proyectar está dividido en dos partes esenciales: El problema creativo que plantea la necesidad de buscar soluciones y el problema de evaluación y toma de decisión que plantea la necesidad de escoger de entre todas las soluciones generadas, la óptima o la que mejor satisfaga los objetivos. En muchas situaciones, los seres humanos han de tomar decisiones. Las personas que tienen que asumir la responsabilidad de tomar decisiones difíciles cuyas consecuencias influirán en el proyecto o en la organización a la que pertenecen o dirigen, están sometidas a tensiones profesionales y emocionales. Estas decisiones difíciles se caracterizan por observar intereses contrapuestos, tener elementos de incertidumbre, envolver distintas personas en la decisión o bien poseer elementos difícilmente valorables. Desde que en 1965 Lofti Zadeh introdujera el concepto de lo “fuzzy” permitiendo la pertenencia de un elemento a un conjunto de forma gradual, y no de manera absoluta como establece la teoría conjuntista clásica, es decir, admitiendo pertenencias valoradas en el intervalo [0,1] en lugar de en el conjunto . Las aplicaciones y desarrollos basados en este sencillo concepto han evolucionado de tal modo que, hoy en día, es prácticamente imposible calcular el volumen de negocio que generan en todo el mundo. En este contexto, el objetivo general de la presente investigación es ahondar en el estudio de la evaluación de alternativas en el ámbito de la “Soft Computing” y dado que los métodos clásicos resultan ineficientes para problemas de decisión complejos, sobre todo para aquellos casos en los que nos encontremos con criterios de los que solo disponemos de información cualitativa. En este trabajo se presenta un sistema hibrido que recoge las fortalezas de cada una de las métodos clásicos utilizados. Con este propósito se pretende aportar una herramienta de ámbito general mediante un sistema de ayuda a la decisión (SAD) para la evaluación de alternativas de manera que ayude a modelizar distintos tipos de problemas, como podrían ser la evaluación de alternativas en la selección de personal, en la selección de proyectos, etc. Y en particular como ejemplo de aplicación de la investigación aportada se presenta el desarrollo de un SAD para el modelado del problema del ranking de universidades tomando el ámbito de la Ingeniería Industrial.[ENG] The process of solving problems that making a project supposes is divided into two essential parts: the creative problem which poses the need to find solutions, and the problem of evaluation and decision making which implies the need to choose from all the solutions generated, the optimum option, or that which best satisfies the objectives. In many situations, human beings must make decisions. Those people who must accept the responsibility of taking difficult decisions with consequences that will influence the project or the organization they belong to or manage, are subjected to professional and emotional stresses. These difficult decisions are characterised by observing opposing interests having elements of uncertainty, involving different people in the decision or possessing elements which are difficult to value. Since 1965 when Lofti Zadeh introduced the “fuzzy” concept which permitted an element to belong to a set in a gradual way, and not in an absolute way as classical set theory established, that is to say, admitting belonging valued in the interval [0,1] instead of in the set , the applications and developments based on this simple concept have evolved to such an extent that nowadays, it is practically impossible to calculate the volume of business it generates throughout the world. In this context, the general objective of the present investigation is to go deeper into the study of the evaluation of alternatives in the field of “Soft Computing”, given that the classical methods are inefficient for complex decision problems, above all for those cases in which we find ourselves with criteria about which we only have qualitative information. In this work a hybrid system is presented which gathers together the strengths of each of the classical methods used. With this purpose the intention is to provide a general tool by means of a decision support system (DSS) for the evaluation of alternatives in such a way that it helps to modelize different types of problems, such as the evaluation of alternatives in the selection of personnel, in the selection of projects, etc. In particular, as an example of the application of the investigation carried out, the development of a DSS is presented for the modelling of the problem of ranking universities, using the field of Industrial Engineering.Universidad Politécnica de CartagenaPrograma de doctorado en Tecnologías Industriale