Intermittent demand, inventory obsolescence, and temporal aggregation forecasts

Autor: Kamal Sanguri, Sabyasachi Patra, Konstantinos Nikolopoulos, Sushil Punia

Publikováno v: International Journal of Production Research, 2023 [Peer Reviewed Journal]

Forecasting for intermittent demand is considered a difficult task and becomes even more challenging in the presence of obsolescence. Traditionally the problem has been dealt with modifications in the conventional parametric methods such as Croston.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4dd73f3d9c779fb358b2f4f851d26f51
https://doi.org/10.1080/00207543.2023.2199435

Trajectory of research on maritime transportation in the era of digitization

Autor: Sonali Shankar, Surya Prakash Singh, Jing-Xin Dong, Sushil Punia

Publikováno v: Benchmarking: An International Journal. 29:194-216

PurposeThe literature on Maritime Transportation (MT) is experiencing a transition phase where the focus of the research is repositioning. It registered steep growth in recent years with its beginning articles on the concepts of cost minimization to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::75d48db0654cf38b68a80dc9876aad33
https://doi.org/10.1108/bij-05-2020-0272

Predictive analytics for demand forecasting: A deep learning-based decision support system

Autor: Sushil Punia, Sonali Shankar

Publikováno v: Knowledge-Based Systems. 258:109956

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2ec7120f15d6a54cbb0d3f2fb4e2a194
https://doi.org/10.1016/j.knosys.2022.109956

Forecasting container throughput with long short-term memory networks

Autor: Sushil Punia, P. Vigneswara Ilavarasan, Sonali Shankar, Surya Prakash Singh

Publikováno v: Industrial Management & Data Systems. 120:425-441

Purpose Better forecasting always leads to better management and planning of the operations. The container throughput data are complex and often have multiple seasonality. This makes it difficult to forecast accurately. The purpose of this paper is t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::134edd0b13c1c628604bc29c0a3e55e0
https://doi.org/10.1108/imds-07-2019-0370

Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions

Autor: Chrysovalantis Vasilakis, Christos Tsinopoulos, Andreas Schäfers, Konstantinos Nikolopoulos, Sushil Punia

Publikováno v: European Journal of Operational Research
European journal of operational research, 2020, Vol.290(1), pp.99-115 [Peer Reviewed Journal]

Highlights • We provide predictive analytics tools for immediate use during COVID-19. • We use data from the UK, USA, India, Germany, Singapore up to mid-April 2020. • We forecast COVID-19 growth rates at country-level. • We use auxiliary dat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90efba474e285368ec95cba22e838be8