Browsing by Author "Garg, Chandra Prakash"

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Citation - WoS: 12
Citation - Scopus: 17
Assessing and Selecting Sustainable Refrigerated Road Vehicles in Food Logistics Using a Novel Multi-Criteria Group Decision-Making Model
(Elsevier Science inc, 2024) Gorcun, Omer Faruk; Tirkolaee, Erfan Babaee; Kucukonder, Hande; Gargf, Chandra Prakash; Garg, Chandra Prakash
In recent years, food loss and waste (FLW) have become an essential issue at the top of the international community's agenda. Since more people are afflicted by this problem every day, the global population would be forced into poverty and starvation without finding an immediate solution. Therefore, in order to decrease FLW, well-designed and sustainable food and cold supply chains (FCSCs) are needed. Additionally, refrigerated transportation systems can be crucial in developing sustainable supply chains. According to some empirical research, the technological capabilities of reefer vehicles or trailers differ significantly. Thus, selecting the reefer vehicle is a complex decision-making problem and selecting appropriate reefer vehicles may have a critical role in constructing successful supply chain systems and reducing food waste and loss. The current research proposes an efficient, robust and practical decision-making framework that can overcome uncertainties to tackle this decision-making problem. The managerial and strategic implications of the study also aid in decreasing FLW and restructuring FSC for industrial context and support to the UN's sustainable development goals (SDGs). Later, an exhaustive sensitivity analysis was conducted to examine the developed model's validity and application, confirming the model's robustness and dependability.
Citation - WoS: 22
Citation - Scopus: 19
Evaluation of Public Transportation Systems for Sustainable Cities Using an Integrated Fuzzy Multi-Criteria Group Decision-Making Model
(Springer, 2023) Canakcioglu, Mustafa; Kundu, Pradip; Kucukonder, Hande; Gorcun, Omer Faruk; Garg, Chandra Prakash
In this era of increasing demand for mobility and rapid urban growth, there is a pressing need for a public transit system that is safe, fast, reliable, well-connected, and sustainable. Furthermore, it is essential to reduce the external costs associated with urban transportation, including environmental pollution, noise, congestion, and accidents, to foster sustainable cities. Choosing the right urban transportation system can meet this goal, but it is not an accessible business for decision-makers in the face of several conflicting criteria and ambiguities in the evaluation process. To cope with this, the current paper suggests a multi-criteria group decision-making (MCGDM) framework consisting of fuzzy BWM (Best-Worst method) and fuzzy MAIRCIA (Multi-Attribute Ideal-Real Comparative Analysis) techniques. This extended MCGDM approach has been applied to evaluate six urban transport systems, namely, Trams, Light Rail Trams, Metro (Subway), Bus Rapid Transport, Commuter Trains, and Public Buses based on 11 selection criteria which we have determined after consultation with highly experienced professionals. The fuzzy BWM technique is employed to identify the weights of the criteria. The fuzzy MAIRCA technique is utilized for ranking the alternatives using the calculated weights of the criteria. The proposed approach's validation has been examined with an extensive robustness check. The study is conducted from a general perspective, i.e., not restricted to a particular city. However, with the identified selection criteria, the proposed decision-making procedure can be repeated for a specific city considering any specific requirements, constraints, or limitations of that city.
Citation - WoS: 22
Citation - Scopus: 19
Evaluation of Public Transportation Systems for Sustainable Cities Using an Integrated Fuzzy Multi-Criteria Group Decision-Making Model
(Springer, 2023) Kundu, Pradip; Gorcun, Omer Faruk; Garg, Chandra Prakash; Kucukonder, Hande; Canakcioglu, Mustafa
In this era of increasing demand for mobility and rapid urban growth, there is a pressing need for a public transit system that is safe, fast, reliable, well-connected, and sustainable. Furthermore, it is essential to reduce the external costs associated with urban transportation, including environmental pollution, noise, congestion, and accidents, to foster sustainable cities. Choosing the right urban transportation system can meet this goal, but it is not an accessible business for decision-makers in the face of several conflicting criteria and ambiguities in the evaluation process. To cope with this, the current paper suggests a multi-criteria group decision-making (MCGDM) framework consisting of fuzzy BWM (Best-Worst method) and fuzzy MAIRCIA (Multi-Attribute Ideal-Real Comparative Analysis) techniques. This extended MCGDM approach has been applied to evaluate six urban transport systems, namely, Trams, Light Rail Trams, Metro (Subway), Bus Rapid Transport, Commuter Trains, and Public Buses based on 11 selection criteria which we have determined after consultation with highly experienced professionals. The fuzzy BWM technique is employed to identify the weights of the criteria. The fuzzy MAIRCA technique is utilized for ranking the alternatives using the calculated weights of the criteria. The proposed approach's validation has been examined with an extensive robustness check. The study is conducted from a general perspective, i.e., not restricted to a particular city. However, with the identified selection criteria, the proposed decision-making procedure can be repeated for a specific city considering any specific requirements, constraints, or limitations of that city.
Citation - WoS: 42
Citation - Scopus: 53
An Integrated Fuzzy Mcdm Approach Based on Bonferroni Functions for Selection and Evaluation of Industrial Robots for the Automobile Manufacturing Industry
(Pergamon-Elsevier Science Ltd, 2023) Garg, Chandra Prakash; Gorcun, Omer F.; Kundu, Pradip; Kucukonder, Hande; Prakash Garg, Chandra
In recent years, there have been dramatic changes in manufacturing systems in many industries depending on technological developments. Robotics is one of the essential components of these changes. Today, the usage of robotics in manufacturing processes has become widespread in almost all industries. Also, it has become a very strong desire ever-increasing for even small and medium-sized enterprises at present. Almost all the previous studies emphasized that industrial robot selection is a highly complex decision-making problem as there are many conflicting factors and criteria. Besides, different and advanced specifications of these robotics added by robotic manufacturers have caused to increase the complexities much more. Hence, decision-makers encounter more complicated decision-making problems affected by many uncertainties. Because of that, an integrated fuzzy group MCDM framework can help overcome many ambiguities proposed in the current paper. The proposed fuzzy integrated model consists of the fuzzy SWARA (F-SWARA'B) and the fuzzy CoCoSo (F-CoCoSo'B), which are extended with the help of the Bonferroni function. The model selected the appropriate industrial robotics used in the automotive industry by considering 15 criteria and ten alternatives. According to the result of the study, the three most significant criteria have been determined: Working Accuracy, Reaching Distance, and Performance; and the most suitable option is the A8. The obtained results were validated with the help of a comprehensive sensitivity analysis consisting of different 150 scenarios. The results are also compared with some existing techniques. The sensitivity analysis results approve the validity and applicability of the proposed model.
Citation - WoS: 6
Citation - Scopus: 6
A Novel Model Based on the Fuzzy Grey Relational Analysis (f-Gra) Approach for Selecting the Appropriate High-Speed Train Set
(Springer, 2023) Garg, Chandra Prakash; Gorcun, Omer F.; Kucukonder, Hande
The high-speed train (HST) system is one of the most critical components of national and international passenger transportation networks. Selecting the appropriate train sets is a critical task for railway operators to build an efficient, productive, safe, inexpensive and environmentally friendly passenger transport network system. On the other hand, selecting the proper HST set is a highly complex process since many conflicting criteria, and decision alternatives make it difficult for decision-makers. This paper suggests the fuzzy Grey Relational Analysis technique. In addition, the fuzzy technique proposed in the current paper has been implemented in two ways: using both the experts' linguistic evaluations and crisp numbers to compare real numerical values and fuzzy evaluations. A comprehensive sensitivity analysis was then conducted to assess the validation of the proposed fuzzy technique and its results in applying this method. The decision alternative of A8 Siemens is the best option for all scenarios, and it has been observed that there are slight differences, which cannot change the overall result in the ranking positions of the options. The analysis results prove that the fuzzy method can be applied to solve these complicated decision-making problems and that the obtained results are robust, accurate, applicable, and realistic.