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

SUSTAINABILITY ASSESSMENT OF TEXTILE AND APPAREL SECTOR: A REVIEW OF CURRENT APPROACHES AND TOOLS

The purpose of this study is to provide an overview of sustainability evaluation techniques in textile and apparel sector. The review study summarizes the different dimension covered, weightage, number of indicators involved, and highlight the weakness and strength of the previous developed sustainability assessment methods in the textile industry. The analysis revealed that majority of the product-related assessment methods prioritised environmental factors only, while all the presentations reviewed in this category neglected triple bottom line (TBL) in their assessment approach. Nevertheless, there is still a need to focus more on integrated assessment tools to fulfil the TBL goals. Environmental assessment methods are comparably advanced and standardized in the field of textile and apparel. However, from the uncertainty’s perspectives, only integrated assessment tools considered fuzziness, grey and stochastic ambiguities in some of their methods, whereas product related assessment tools studied, ignored fuzziness and grey uncertainties completely. This current study offers comprehensive details of product related assessment and integrated assessment methods that was published from 2010 to 2022. Furthermore, examined current sustainability evaluation methods and offered insights into how sustainability assessment techniques have evolved in the textile and clothing industry

A novel financial risk assessment model for companies based on heterogeneous information and aggregated historical data

The financial risk not only affects the development of the company itself, but also affects the economic development of the whole society; therefore, the financial risk assessment of company is an important part. At present, numerous methods of financial risk assessment have been researched by scholars. However, most of the extant methods neither integrated fuzzy sets with quantitative analysis, nor took into account the historical data of the past few years

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

Performance assessment of circular economy for phosphorus chemical firms based on VIKOR-QUALIFLEX method

Confronting the dilemma of resource shortage and environmental pollution, the idea of circular economy (CE) has attracted widespread attentions. To address these problems, several industrial companies have incorporated the CE in their operation or design. In this sense, the phosphorus chemical firms (PCFs) are promoting CE to achieve sustainable development goals since phosphorus is a non-renewable resource and one of the nutrient elements essential for crop growth. Thus, this paper aims to find a suitable way to assess the performance of CE for PCFs. Firstly, the evaluation index system of CE is designed according to the characteristics of CE for PCFs

A Supplier Selection Model Using Alternative Ranking Process by Alternatives’ Stability Scores and the Grey Equilibrium Product

open access articleSupply chain management begins with supplier evaluation and selection. The supplier selection deals with various criteria with different contexts which makes it a complex multi-criteria decision-making (MCDM) method. In this paper, a novel MCDM method, called the alternative ranking process by alternatives’ stability scores (ARPASS), is proposed to solve supplier selection problems. ARPASS considers each alternative as a system that is constructed on integrated components. To perform properly, a system requires high integrity and stability. ARPASS utilizes the stability of alternatives as an effective element for ranking the alternatives. The ARPASS is developed in two forms, ARPASS and ARPASS*. The new method utilizes standard deviations and Shannon’s entropy to compute the alternatives’ stabilities. In this paper, in addition to the new MCDM methods, a new method called the grey equilibrium product (GEP) is introduced to convert grey linguistic variables into crisp values, using decision makers’ subjective perceptions and judgments. To highlight and validate the novel methods’ performance, they are applied to two sustainable supplier selection problems. For evaluation of the reliability of ARPASS and ARPASS*, their results were compared with the results of the popular MCDM methods. We compared the methods in terms of calculation time, simplicity, transparency, and information type

An extended COPRAS model for multi-criteria decision-making problems and its application in web-based hotel evaluation and selection

Facilitation of suitable accommodation for different travellers is the prime concern of travel agencies. Travel agencies must keep themselves competitive and sustain a good pace of growth to continue raising profits by attracting and retaining as many tourists as possible through meeting their various prospective needs. To achieve this, the agencies must prepare well-organised data for hotels and destinations from a quality control perspective. Initially, the hotels are ranked and evaluated according to performance across several criteria from the tourists’viewpoint. The relative importance of each criterion is mainly subjective and depends on the assessor’s judgement. Additionally, hotels’ rankings vary across different websites, resulting in inconsistencies. To handle such inconsistencies and subjectivity, this paper presents a collective decision-making evaluation framework by integrating a weighted interval rough number (WIRN) method and a WIRN- based complex proportional assessment (COPRAS) model to evaluate and rank hotels. An empirical example and a real-world case study from the Indian tourism industry are presented to validate the applicability of the proposed framework. Finally, a comparison and sensitivity analysis are performed to examine the validity and robustness of the proposed model

Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling

In the last decade, the Industrial Revolution 4.0 brought flexible supply chains and flexible design projects to the forefront. Nevertheless, the recent pandemic, the accompanying economic problems, and the resulting supply problems have further increased the role of logistics and supply chains. Therefore, planning and scheduling procedures that can respond flexibly to changed circumstances have become more valuable both in logistics and projects. There are already several competing criteria of project and logistic process planning and scheduling that need to be reconciled. At the same time, the COVID-19 pandemic has shown that even more emphasis needs to be placed on taking potential risks into account. Flexibility and resilience are emphasized in all decision-making processes, including the scheduling of logistic processes, activities, and projects

Fuzzy Techniques for Decision Making 2018

Zadeh's fuzzy set theory incorporates the impreciseness of data and evaluations, by imputting the degrees by which each object belongs to a set. Its success fostered theories that codify the subjectivity, uncertainty, imprecision, or roughness of the evaluations. Their rationale is to produce new flexible methodologies in order to model a variety of concrete decision problems more realistically. This Special Issue garners contributions addressing novel tools, techniques and methodologies for decision making (inclusive of both individual and group, single- or multi-criteria decision making) in the context of these theories. It contains 38 research articles that contribute to a variety of setups that combine fuzziness, hesitancy, roughness, covering sets, and linguistic approaches. Their ranges vary from fundamental or technical to applied approaches