A hybrid MCDM-fuzzy multi-objective programming approach for a G-Resilient supply chain network design

Stakeholders are being increasingly encouraged to improve their supply chain risk management in order to cope efficiently and successfully with disruption risks due to unexpected events. Notwithstanding, supply chain managers lagged behind this target overlooking green development in considering environmental impact which has become a main criterion in supply chain management. Where the era of greenness threatens current supply chain partners with the need to either cope with the new green regulations or leave the field for new players. Thus, an approach to design supply chains that are simultaneously resilient, and green is needed. This study satisfies this need by developing a green and resilient (G-resilient, here after) fuzzy multi-objective programming model (GR-FMOPM) to present a G-resilient supply chain network design in determining the optimal number of facilities that should be established. The objectives are minimization of total cost and environmental impact and maximization of Value of resilience pillars where Redundancy, Agility, Leanness and Flexibility (V-RALF) can be seen four of main pillars required for supply chain resilience. Fuzzy AHP is used for determining the importance weight for each pillar followed by a usage of a Fuzzy technique for assigning the importance weight for each potential facility with respect to RALF. The importance weights obtained by Fuzzy AHP and the Fuzzy technique are then integrated in the third objective (maximization of V-RALF) to maximize the value of resilience pillars. Based on the fuzzy multi-objective model, the ε-constraint method is used to reveal Pareto optimal solutions and TOPSIS was then used to select the final Pareto solution. A case study is used to validate the applicability of the developed GR-FMOPM in obtaining a G-resilient supply chain network design and a trade-off among economic, green and resilience objectives. Finally, a sensitivity analysis is performed on the importance weight for facilities Pareto solutions with respect to the importance weight of RALF. Research findings proved that the developed GR-FMOPM could be used as a tool in evaluating and ranking related facilities with respect to their resilience performance. It can also be used to obtain a G-resilient supply chain network design in terms of facilities that should be established towards a trade-off among the three aforementioned objectives

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

Investigation on Multi-Criteria Decision Making Methods Application in Sustainable Product Design

Background: Integrating sustainability development' aspects in the design process is becoming, a growth area in companies. Consequently, sustainable product design has to consider the different aspects of sustainability throughout its life cycle phases in addition of other requirements. This integration is becoming more complicated due the difficulty of managing the constraints and alternatives related to the product and stakeholders needs. This study aims to highlights the most used Multi-Criteria Decision Making (MCDM) tools and methods used in sustainable product design process. Contribution: Product design process involves interesting decisional tasks such as the choice of materials, standard parts, technical solutions. Hence, the contribution of this work is to help designer to adopt relevant MCDM tools and methods that can be integrated to other tools to facilitate and to justify their decisional tasks. Method: Several methods have been affected to solve the problems related to this complexity such as MCDM. A literature review was conducted based on Siencedirect and GoogleScholar articles databases. After filtering more than 200 articles only 62 articles were considered to analyze the correlation between sustainable product design and MCDM. Results: Classified MCDM use according to the type of choices to achieve SPD goals. This paper allowed us to find matches between MCDM methods and SPD problem. The majority of case studies result show that a large portion of sustainable design methods, techniques, and tools are applied to the sustainable product’ along its different life cycle phases Conclusion: It is noticed that the use of MCDM methods are an important outcome in the sustainable product design process and deeply helps designers to make suitable choices. Also, several matches relating MCDM, other methods and sustainable product design sphere are discusse

Enhancing the cosmetics industry sustainability through a renewed sustainable supplier selection model

The cosmetics industry requires a long-term sustainable strategy to balance its continuously growing trend worldwide and its resources consumption. In this view, the suppliers' selection process is gaining more attention affecting products' overall sustainability. The objective of this contribution is hence to develop and validate the Cosmetics Sustainable Supplier Selection (C-SSS) model allowing the selection of sustainable suppliers for the cosmetic industry, evaluating them in an objective and balanced manner. The model was built relying on both scientific and grey literature, by incorporating the characteristics of existing SSS models usually used separately. The C-SSS enabled to integrate the EMM approach (to reduce the subjectivity), the ANP approach (to evaluate criteria interconnections), and the TOPSIS and ELECTRE models (to create a hybrid compensation model) to support managers in objectively selecting the most sustainable suppliers. The C-SSS model was applied and validated through an industrial use case in a cosmetics Italian company

Gresilient supplier assessment and order allocation planning

Companies are under pressure to re-engineer their supply chains to ‘go green’ while simultaneously improving their resilience to cope with unexpected disruptions where the supplier selection decision plays a strategic role. We present a new approach to supplier evaluation and allocating the optimal order quantity from each supplier with respect to green and resilience (Gresilience) characteristics. An integrated framework that considers traditional business, green and resilience criteria and sub-criteria was developed, followed by a calculation of importance weight of criteria and sub-criteria using analytical hierarchy process (AHP). We evaluate suppliers using the technique for order of preference by similarity to ideal solution (TOPSIS). The obtained weights from AHP and TOPSIS were integrated into a developed multi-objective programming model used as an order allocation planner and the ε-constraint method was used to solve the multi-objective optimization problem. TOPSIS was applied to select the final Pareto solution based on its closeness from the ideal solution. The applicability and effectiveness of the proposed approach was illustrated using a real case study through a comparatively meaningful ranking of suppliers. The study provides a helpful aid for managers seeking to improve their supply chain resilience along with ‘go green’ responsibilities

Combining Multi-Criteria Decision Making (MCDM) Methods with Building Information Modelling (BIM): A Review

Integrating building information to support decision-making has been a key challenge in the Architecture, Engineering, and Construction (AEC) industry. The synergy of Building Information Modelling (BIM) and Multi-Criteria Decision Making (MCDM) is expected to improve information integration and decision-making. The aim of this paper is to identify strategies to improve the synergy between MCDM and BIM. From the earliest literature (2009) to the present, this study examines 45 articles combining MCDM with BIM. We find that the five major application domains are sustainability, retrofit, supplier selection, safety, and constructability. Five established strategies for improving the synergy between MCDM and BIM were discussed and can be used as a benchmark for evaluating the application of decision techniques in practice. This study points out gaps of combining MCDM and BIM in the current literature. It also sheds new light into combining MCDM with BIM for practitioners, as to promote integrated decision-making

Serial-integrated multi-criteria decision-making technique for resilient supplier selection in the manufacturing industry

A supply chain is an entire system of producing and delivering a product or service, from the very beginning stage of sourcing raw material to the final stage of delivering a product or service to end-users. Several global risks and disruptions brought massive and devastating impacts on the world economy including the Small and Medium Enterprises (SMEs). Since the supplier is one of the important elements in a supply chain, economic resilience can be implemented by selecting a resilient supplier. However, the literature shows that previous supplier selections only focused on traditional, green and sustainable suppliers’ criteria but resilience was rare to be discussed. Thus, the first objective of the study is to identify the generic criteria for selecting resilient suppliers. At the same time, there are problems in dealing with uncertainties and incomplete information while selecting suppliers. The second objective is to develop a new integrated Multi-Criteria Decision-Making (MCDM) model that considers incomplete data and uncertainties in selecting resilient suppliers. In this study, the proposed criteria were quality, lead time, cost, flexibility, visibility, responsiveness and financial stability. A serial-integrated MCDM technique was proposed by combining Grey Relational Analysis (GRA) from the grey theory and the Best Worst Method-Technique for Order Preference by Similarity to an Ideal Solution (BMW-TOPSIS) technique in serial to assess the suppliers and select the best alternative. The proposed criteria and technique were applied in the metal manufacturing company (Case 1) and the food manufacturing company (Case 2) which were facing economic problems to demonstrate its effectiveness. The result was generated using MATLAB. The result for Case 1 shows that Financial Stability has the largest weight and Supplier 1 is the best supplier for the company. For Case 2, Cost shows the largest weight, and the best supplier is Supplier 4. Then, the result was verified through manual calculation and validated with Analytic Hierarchy Process-VlseKriterijumska Optimizacija I Kompromisno Resenje (AHP-VIKOR). Through the identification of the generic resilience criteria and the suitable MCDM model, the managers can focus on resilience with the consideration of uncertainties and incomplete information to improve the supplier selection process. This can help to raise the supply chain performance of the companies

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