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9. How to use no-code artificial intelligence to predict and minimize the inventory distortions for resilient supply chains.

Author

Jauhar, Sunil Kumar, Jani, Shashank Mayurkumar, Kamble, Sachin S., Pratap, Saurabh, Belhadi, Amine, and Gupta, Shivam

Subjects
MACHINE learning, ARTIFICIAL intelligence, SUPPLY chains, INVENTORY control, ELECTRONIC commerce, INVENTORIES, SUPPLY chain disruptions
Abstract

Consumers' dramatic demand has a pernicious effect throughout the supply chain. It exacerbates inventory distortion because of significant revenue loss caused by stock-level issues. Despite the availability of several forecasting techniques, large organisations, manufacturing firms, and e-commerce websites collectively lose around $1.8 trillion annually to inventory distortion. If this problem is solved, sales may increase by 10.3 percent. The businesses are concerned about mitigating this loss. Artificial intelligence (AI) can play a significant role in building resilient supply chains. However, developing AI models consumes time and cost. In this paper, we propose a No Code Artificial Intelligence (NCAI) enabling non-technical companies to build machine learning models based on production quantity and inventory replenishment. The development of the NCAI model is fast and inexpensive. However, little research deals with applying NCAI to operations and supply chain problems. Addressing the existing gap, we show the application of NCAI in the retail industry. [ABSTRACT FROM AUTHOR]

Published
2024
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12. Indian Postal Service Quality Assessment Using Graph Theoretic Approach – A Quantitative Decision-Making Tool

Author

Vadivel, S. M., Sequeira, A. H., Jauhar, Sunil Kumar, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Pllana, Sabri, editor, Casalino, Gabriella, editor, Ma, Kun, editor, and Bajaj, Anu, editor

Published
2023
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17. Tamilnadu Omnibus Travels Evaluation Using TOPSIS and Fuzzy TOPSIS Methods

Author

Vadivel, S. M., Sequeira, A. H., Jauhar, Sunil Kumar, Chandana, V., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Madureira, Ana Maria, editor, Kaklauskas, Arturas, editor, Gandhi, Niketa, editor, Bajaj, Anu, editor, Muda, Azah Kamilah, editor, Kriksciuniene, Dalia, editor, and Ferreira, João Carlos, editor

Published
2022
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18. Postal Service Shop Floor—Facility Layout Evaluation and Selection Using Fuzzy AHP Method

Author

Vadivel, S. M., Sequeira, A. H., Jauhar, Sunil Kumar, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Sharma, Tarun K., editor, Ahn, Chang Wook, editor, Verma, Om Prakash, editor, and Panigrahi, Bijaya Ketan, editor

Published
2022
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24. CNC Machine Shop Floor Facility Layout Design Using Genetic Algorithm

Author

Vadivel, S. M., Sequeira, A. H., Jauhar, Sunil Kumar, Amirthagadeswarn, K. S., Aravind Krishna, T., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Pant, Millie, editor, Kumar Sharma, Tarun, editor, Arya, Rajeev, editor, Sahana, B.C., editor, and Zolfagharinia, Hossein, editor

Published
2020
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25. Application of Multi-criteria Decision-Making Method for the Evaluation of Tamilnadu Private Bus Companies

Author

Vadivel, S. M., Sequeira, A. H., Jauhar, Sunil Kumar, Baskaran, R., Robert Rajkumar, S., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Pant, Millie, editor, Kumar Sharma, Tarun, editor, Arya, Rajeev, editor, Sahana, B.C., editor, and Zolfagharinia, Hossein, editor

Published
2020
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26. Metaheuristic for Optimize the India Speed Post Facility Layout Design and Operational Performance Based Sorting Layout Selection Using DEA Method

Author

Vadivel, S. M., Sequeira, A. H., Jauhar, Sunil Kumar, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Abraham, Ajith, editor, Cherukuri, Aswani Kumar, editor, and Gandhi, Niketa, editor

Published
2020
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35. Estimating Technical Efficiency of Academic Departments: Case of Government PG College

Author

Ali, Imran, Rana, U. S., Pant, Millie, Jauhar, Sunil Kumar, Mogha, Sandeep Kumar, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Pant, Millie, editor, Ray, Kanad, editor, Sharma, Tarun K., editor, Rawat, Sanyog, editor, and Bandyopadhyay, Anirban, editor

Published
2018
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42. A DEA-ANN-based analytical framework to assess and predict the efficiency of Canadian universities in a service supply chain context.

Author

Jauhar, Sunil Kumar, Zolfagharinia, Hossein, and Amin, Saman Hassanzadeh

Subjects
SUPPLY chains, DATA envelopment analysis, ARTIFICIAL neural networks, SUPPLY chain management, DOCTOR of philosophy degree, UNIVERSITY rankings
Abstract

Purpose: This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities. Design/methodology/approach: The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance. Findings: The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs. Research limitations/implications: This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities. Practical implications: The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings. Originality/value: This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended. [ABSTRACT FROM AUTHOR]

Published
2023
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46. An Approach to Solve Multi-criteria Supplier Selection While Considering Environmental Aspects Using Differential Evolution

Author

Jauhar, Sunil Kumar, Pant, Millie, Deep, Aakash, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Panigrahi, Bijaya Ketan, editor, Suganthan, Ponnuthurai Nagaratnam, editor, Das, Swagatam, editor, and Dash, Shubhransu Sekhar, editor

Published
2013
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