DECISION SUPPORT SYSTEM FOR MANAGING AND DETERMINING INTERNATIONAL CLASS PROGRAM: GA AND AHP APPROACH

This study proposes a new method, a hybrid model for managing and determining the proposed International class based on many criteria of academic performance in university. The approach has been implemented as a decision support system allowing evaluation of various criteria and scenarios. The new model combines two different methods in decision support system: Analytical hierarchy Process (AHP) and Grey Analysis, the proposed model uses the AHP pairwise comparisons and the measure scale to generate the weights for the criteria which are much better and guarantee more fairly preference of criteria. Applying the system as decision-support facility for the management has resulted in significant acceleration of planning procedures and implementation, raised the overall effectiveness with respect to the underlying methodology and ultimately enabled more efficient academic administration

Multi-criteria decision making approach for vendor selection

In the present study an efficient Multi-Criteria Decision Making (MCDM) approach has been proposed for quality evaluation and performance appraisal in vendor selection. Vendor selection is a Multi-Criteria Decision Making (MCDM) problem influenced by multiple performance criteria/attributes. These criteria attributes may be both qualitative as well as quantitative. Qualitative criteria estimates are generally based on previous experience and expert opinion on a suitable conversion scale (Likert Scale). This conversion is based on human judgment;therefore, predicted result may not be accurate always because the method doesn’t explore real data. These are analyzed using AHP, QFD, Fuzzy techniques etc. reported in literature. In solution of MCDM problems there should be a common trend is to convert quantitative criteria values into an equivalent single performance index called Multi-attribute Performance Index (MPI). Benchmarking and selection of the best alternative can be made in accordance with the MPI values of all the alternatives. In this context, present study highlights application of VIKOR method adapted from MCDM for utilizing quantitative real performance estimate scores. Detail methodology of VIKOR method has been illustrated in this reporting through a case study

Selection of safety officers in an indian construction organization by using grey relational analysis

Stakeholders are responsible for implementing the occupational health and safety provisions in an organization. Irrespective of organization, the role of safety department is purely advisory as it coordinates with all the departments, and this is crucial to improve the performance. Selection of safety officer is vital job for any organization; it should not only be based on qualifications of the applicant, the incumbent should also have sufficient exposure in implementing proactive measures. The process of selection is complex and choosing the right safety professional is a vital decision. The safety performance of an organization relies on the systems being implemented by the safety officer. Application of multi criteria decision-making tools is helpful as a selection process. The present study proposes the grey relational analysis(GRA) for selection of the safety officers in an Indian construction organization. This selection method considers fourteen criteria appropriate to the organization and has ranked the results. The data was also analyzed by using technique for order Preference by Similarity to an Ideal solution (TOPSIS) and results of both the methods are strongly correlate

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

A Fuzzy ANP Based Grey Relational Approach to Evaluate CRM System in Context of Bangladesh

This study aims to select a suitable CRM (customer relationship management) system among different possible alternatives for organization’s in Bangladesh. Since, evaluating CRM system on the basis of lot of attributes leads us to Multiple-criteria decision analysis (MCDA) problems. In this study, a hybrid MCDA models were used. FuzzyANP (Analytic Network Process) and GRA (Grey Relational Analysis) approaches were adopted to solve the problem. The study explored that the Hubspot CRM was optimal solution in context of Bangladesh. Our research will beneficial to the organizing for better customer support. As far our knowledge goes, this is the first attempt to select CRM softwares in context of Bangladesh. Keywords: Analytic network process; Customer relationship management system; Grey relational analysis; Multiple-criteria decision analysis DOI: 10.7176/IKM/11-4-06 Publication date:June 30th 202

Supplier Evaluation with Environmental Aspects and Common DEA Weights

Supplier selection is an important business decision. Beside traditional management criteria the environmental aspects are getting often recognition. In this paper the method of Data Envelopment Analysis (DEA) is used to study the extension of traditional supplier selection methods with environmental factors. The focus will be on the weight selection process which can control the selection. In this method we divide the criteria in two manners: the traditional and environmental (green) factors. Then with the help of DEA we are searching a weight system with which the environmental criteria can influence the decision with a representation of the green factors. To choose the mentioned weight system, we apply DEA (Data Envelopment Analysis) with common weights analysis (CWA) method. In this case of DEA/CWA the common weights are calculated with a linear programming problem

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

A hybrid method of GRA and DEA for evaluating and selecting efficient suppliers plus a novel ranking method for grey numbers

Purpose: Evaluation and selection of efficient suppliers is one of the key issues in supply chain management which depends on wide range of qualitative and quantitative criteria. The aim of this research is to develop a mathematical model for evaluating and selecting efficient suppliers when faced with supply and demand uncertainties. Design/methodology/approach: In this research Grey Relational Analysis (GRA) and Data Envelopment Analysis (DEA) are used to evaluate and select efficient suppliers under uncertainties. Furthermore, a novel ranking method is introduced for the units that their efficiencies are obtained in the form of interval grey numbers. Findings: The study indicates that the proposed model in addition to providing satisfactory and acceptable results avoids time-consuming computations and consequently reduces the solution time. To name another advantage of the proposed model, we can point out that it enables us to make decision based on different levels of risk. Originality/value: The paper presents a mathematical model for evaluating and selecting efficient suppliers in a stochastic environment so that companies can use in order to make better decisions.Peer Reviewe