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2020 – today
- 2024
[j11]Tariq Aljuneidi
, Sushil Punia, Aida Jebali, Konstantinos Nikolopoulos:
Forecasting and planning for a critical infrastructure sector during a pandemic: Empirical evidence from a food supply chain. Eur. J. Oper. Res. 317(3): 936-952 (2024)- [j10]Kamal Sanguri, Sabyasachi Patra, Konstantinos Nikolopoulos, Sushil Punia:
Intermittent demand, inventory obsolescence, and temporal aggregation forecasts. Int. J. Prod. Res. 62(5): 1663-1685 (2024) - 2023
- [j9]Kamal Sanguri, Sabyasachi Patra, Sushil Punia:
Forecast reconciliation in the temporal hierarchy: Special case of intermittent demand with obsolescence. Expert Syst. Appl. 218: 119566 (2023) - 2022
- [j8]Kamal Sanguri, Sonali Shankar, Sushil Punia, Sabyasachi Patra:
Hierarchical container throughput forecasting: The value of coherent forecasts in the management of ports operations. Comput. Ind. Eng. 173: 108651 (2022) - [j7]Sushil Punia, Sonali Shankar:
Predictive analytics for demand forecasting: A deep learning-based decision support system. Knowl. Based Syst. 258: 109956 (2022) - 2021
- [j6]Konstantinos Nikolopoulos, Sushil Punia, Andreas Schäfers, Christos Tsinopoulos, Chrysovalantis Vasilakis:
Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions. Eur. J. Oper. Res. 290(1): 99-115 (2021) - [j5]Sonali Shankar, Sushil Punia, P. Vigneswara Ilavarasan:
Deep learning-based container throughput forecasting: a triple bottom line approach. Ind. Manag. Data Syst. 121(10): 2100-2117 (2021) - 2020
- [j4]Sushil Punia, Surya Prakash Singh, Jitendra K. Madaan:
A cross-temporal hierarchical framework and deep learning for supply chain forecasting. Comput. Ind. Eng. 149: 106796 (2020) - [j3]Sushil Punia, Surya Prakash Singh, Jitendra K. Madaan:
From predictive to prescriptive analytics: A data-driven multi-item newsvendor model. Decis. Support Syst. 136: 113340 (2020) - [j2]Sushil Punia, Konstantinos Nikolopoulos, Surya Prakash Singh, Jitendra K. Madaan, Konstantia Litsiou:
Deep learning with long short-term memory networks and random forests for demand forecasting in multi-channel retail. Int. J. Prod. Res. 58(16): 4964-4979 (2020) - [j1]Sonali Shankar, P. Vigneswara Ilavarasan, Sushil Punia, Surya Prakash Singh:
Forecasting container throughput with long short-term memory networks. Ind. Manag. Data Syst. 120(3): 425-441 (2020)
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