Bijoy Krishna Debnath
@tezu.ernet.in/appsc
Assistant Professor, Department of Applied Sciences
Tezpur University
EDUCATION
Ph.D. (Mathematics), 2019
National Institute of Technology Agartala
Master of Science (Mathematics), 2015
Gauhati University
Bachelor of Science (Mathematics), 2013
Tripura University
RESEARCH INTERESTS
Deterministic and Fuzzy Inventory Modelling, Supply Chain Models, Imperfect Manufacturing Systems
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Brajamohan Sahoo and Bijoy Krishna Debnath
Elsevier BV
Brajamohan Sahoo and Bijoy Krishna Debnath
Springer Science and Business Media LLC
Brajamohan Sahoo and Bijoy Krishna Debnath
Springer Science and Business Media LLC
Puspendu Giri, Bijoy Krishna Debnath, and Somnath Paul
Elsevier BV
Brajamohan Sahoo and Bijoy Krishna Debnath
Elsevier BV
Tanmay Halder and Bijoy Krishna Debnath
Elsevier BV
Ajoy Kanti Das, Nandini Gupta, Rajat Das, Suman Das, Rakhal Das, Carlos Granados, and Bijoy Krishna Debnath
IGI Global Scientific Publishing
In an increasingly globalized economy, businesses must engage diverse consumer groups with unique preferences and cultural nuances. Traditional marketing strategies, relying on rigid segmentation and deterministic data analysis, often fail to capture the complexities of multicultural consumer behavior. This chapter examines fuzzy logic's function in diversity-driven marketing, providing a versatile framework for managing ambiguous and subjective customer data. Fuzzy multi-criteria decision-making (MCDM) techniques like fuzzy AHP and fuzzy TOPSIS can be used to help organizations optimize marketing tactics based on emotional engagement, linguistic appeal, and cultural relevance. Three global marketing campaigns—universal, localized, and hybrid—are evaluated in a case study, showing how localized storytelling raises brand engagement and trust. The study also emphasizes real-time optimization, in which marketing techniques are continuously improved by fuzzy logic in response to changing customer interactions.
Brajamohan Sahoo, Bijoy Krishna Debnath, and Abhijit Saha
EDP Sciences
In modern supply chain management, selecting sustainable agile suppliers is essential. This approach integrates agile practices with sustainability principles to build resilient, eco-friendly supplier networks. It enhances competitiveness, reduces environmental impact, and supports effective supply chain risk management. By prioritizing environmental, social, and economic factors in supplier selection, organizations can form lasting partnerships that align with sustainability goals and remain adaptable to shifting market demands. This study aims to identify the optimal supplier for a Sustainable Agile Manufacturing process by incorporating insights from three decision-makers and evaluating five alternatives based on 20 specific criteria. In this article two integrated Multi-Criteria Decision Making (MCDM) model proposed within Pythagorean fuzzy (PF) environment to identify the optimal supplier for sustainable agile manufacturing. First, the Pythagorean fuzzy MEthod based on the Removal Effects of Criteria (MEREC) method is used to calculate objective criteria weights, followed by the Pythagorean fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to determine subjective criteria weights. Then, the Pythagorean fuzzy Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) and Pythagorean fuzzy Multi-Attributive Border Approximation area Comparison (MABAC) methods are applied to finalize the selection of the most suitable supplier. The results of this study indicate that the 4th alternative is the optimal supplier for a sustainable, agile manufacturing process. Additionally, this article explores the interdependencies among criteria and provides comprehensive sensitivity and comparison analysis, along with insights into the managerial implications of this research.
Tanmay Halder and Bijoy Krishna Debnath
Elsevier BV
Ajoy Kanti Das, Nandini Gupta, Takaaki Fujita, Suman Das, Carlos Granados, Bijoy Krishna Debnath, and Rakhal Das
IGI Global Scientific Publishing
The convergence of luxury branding and smart technology has led to a new paradigm in strategic co-branding. This chapter introduces a Multi-Criteria Decision-Making (MCDM) framework that integrates Neutrosophic Sets to address uncertainty, hesitation, and conflicting expert opinions in evaluating smart luxury co-branding partnerships. Traditional decision-making models often fail to capture the complexities of consumer perception, technological integration, and market acceptance, which involve varying degrees of truth, indeterminacy, and falsity. Neutrosophic MCDM enhances decision robustness by incorporating Neutrosophic Weighted Aggregation Operators and Similarity Measures to quantify brand synergy and compatibility. Case studies, including collaborations between luxury brands and technology firms, illustrate the framework's application in selecting optimal co-branding partners. The findings demonstrate that the Neutrosophic approach provides a more nuanced and data-driven methodology for evaluating strategic alliances in the smart luxury sector, ensuring informed MCDM.
Ömer Faruk Görçün, Abhijit Saha, Pydimarri Venkata Ravi Kumar, and Bijoy Krishna Debnath
Elsevier BV
Sourav Mahata and Bijoy Krishna Debnath
Elsevier BV
Brajamohan Sahoo and Bijoy Krishna Debnath
CRC Press
Abhijit Saha, Arunodaya Raj Mishra, Pratibha Rani, Muhammet Deveci, Bijoy Krishna Debnath, Norziana Jamil, and Moamin A. Mahmoud
Elsevier BV
Brajamohan Sahoo and Bijoy Krishna Debnath
Elsevier BV
Puspendu Giri, Somnath Paul, and Bijoy Krishna Debnath
Elsevier BV
Brajamohan Sahoo and Bijoy Krishna Debnath
IGI Global
Selecting the ideal location for regenerative tourism is vital for environmental preservation and sustainable progress. Destination choice significantly impacts regenerative initiatives' effectiveness, affecting ecological benefits and socio-economic outcomes. A well-selected site fosters ecosystem restoration and positive engagement with indigenous communities, leveraging tourism as a force for biodiversity preservation, carbon capture, and local empowerment. In this chapter, the fuzzy multi-attributive border approximation area comparison (MABAC) approach is utilized to select the optimal site for regenerative tourism initiatives, considering six criteria each with five alternatives and input from three decision-makers. Normalization occurs after forming the initial decision matrix, followed by weight normalization. Performance index and rank are determined using the fuzzy multi-attributive border approximation area comparison (MABAC) procedure. Ultimately, after careful evaluation and consideration, it becomes evident that the fifth alternative stands out as the most suitable location for implementing regenerative practices in the field of tourism.
Abhijit Saha, Bijoy Krishna Debnath, Prasenjit Chatterjee, Annapurani K. Panaiyappan, Surajit Das, and Gogineni Anusha
Elsevier BV
Puspendu Giri, Somnath Paul, and Bijoy Krishna Debnath
Elsevier BV
Bijoy Krishna Debnath, Pinki Majumder, and Uttam Kumar Bera
Inderscience Publishers
Sourav Mahata and Bijoy Krishna Debnath
Elsevier BV
Sourav Mahata and Bijoy Krishna Debnath
EDP Sciences
This paper addresses a single item two-level supply chain inventory model considering deterioration during carrying of deteriorating item from a supplier’s warehouse to a retailer’s warehouse as well as deterioration in the retailer’s warehouse. The model assumes preservation technology in the retailer’s warehouse to prevent the rate of deterioration. An upper limit for the preservation technology investment has been set as a constraint to the model. The model maximizes the retailer’s profit per unit time, simultaneously calculated optimal order quantity. A price dependent demand and storage-time dependent holding cost is considered to develop the model. Some theorems are proven to get optimal values of the total cost. A numerical problem is workout as per the developed algorithm and with the help of MATLAB software to study the applicability of our theoretical results.
Abhijit Saha, Priyanka Majumder, Debjit Dutta, and Bijoy Krishna Debnath
Springer Science and Business Media LLC