S., Srivatsa Srinivas

2025-04, S. Sivanandham, S., Srivatsa Srinivas

Emanating from the food shortages in the 1960s, the public distribution system (PDS) in India has undergone various transformations through the years to expand food security across different regions of the country. Food grains, procured from the farmers, are processed in mills and transported from the central warehouses to the district warehouses and then finally to the fair price shops in the district. Given the district administration's role in managing public distribution operations by contracting with cooperatives who provide logistics services at the last mile, we develop a light-weight and scalable operations research-based decision support system for food grain distribution from the district warehouses to the fair price shops. Our study focusses on the last-mile distribution in the Ramanathapuram district of Tamil Nadu, India wherein the food grains need to be transported from the eight district warehouses associated with different cooperatives to the fair price shops. Given the current mapping of the district warehouses to the fair price shops, we establish the baseline by running the vehicle routing problem for each district warehouse to arrive at the baseline distances for each district warehouse and the entire district. Subsequently, we perform a remapping of the district warehouses to the fair price shops by running a relaxed version of the assignment problem and then run the vehicle routing problem over these revised clusters. Results indicate that 9% savings in total transportation costs is generated with the remapping procedure. Our light-weight decision support system acts as a valuable policy tool to the district administrators in establishing contracts with the cooperatives for each district warehouse, with implications for scaling it across the country. © 2025 Elsevier Ltd

2023-05, S., Srivatsa Srinivas, Rahul R. Marathe

With the advent of COVID-19, urban transportation has been severely disrupted. We develop a stylized analytical model to study the effect of COVID-19 on the optimal pricing and hygiene level decisions of e-hailing taxi services, which play a crucial role in urban transportation. We analyze whether autonomous vehicles can aid the e-hailing taxi firms to sustain operations during these troubled times. In particular, we provide conditions under which the e-hailing taxi firms should collaborate with an original equipment manufacturer to introduce autonomous vehicles for urban transportation. Owing to the high fixed cost associated with acquiring autonomous vehicles, the e-hailing taxi firms intend to collaborate with an original equipment manufacturer. If the e-hailing taxi firm obtains a significant share from each ride in its collaboration, the hygiene level with autonomous vehicles is always greater than the hygiene level without autonomous vehicles, which is vital during the pandemic. With respect to the question of whether the e-hailing taxi firm should collaborate with the original equipment manufacturer to introduce autonomous vehicles from consumers’ viewpoint, we surprisingly find that the consumers are better off when the autonomous vehicles are introduced without collaboration both in the short-run and the long-run. However, given the high fixed cost of introducing autonomous vehicles, the e-hailing taxi firm will find it profitable to collaborate with an original equipment manufacturer if and only if its share from each ride is significant enough. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.

2024, Zakaria El Hathat, V. G. Venkatesh, V. Raja Sreedharan, Tarik Zouadi, Arunmozhi Manimuthu, Yangyan Shi, S., Srivatsa Srinivas

As emphasized in multiple United Nations (UN) reports, sustainable agriculture, a key goal in the UN Sustainable Development Goals (SDGs), calls for dedicated efforts and innovative solutions. In this study, greenhouse gas (GHG) emissions in the groundnut supply chain from the region of Diourbel & Niakhar, Senegal, to the port of Dakar are investigated. The groundnut supply chain is divided into three steps: cultivation, harvesting, and processing/shipping. This work adheres to UN guidelines, addressing the imperative for sustainable agriculture by applying machine learning-based predictive modeling (MLPMs) utilizing the FAOSTAT and EDGAR databases. Additionally, it provides a novel approach using blockchain-enabled off-chain machine learning through smart contracts built on Hyperledger Fabric to secure GHG emissions storage and machine learning’s predictive analytics from fraud and enhance transparency and data security. This study also develops a decision-making dashboard to provide actionable insights for GHG emissions reduction strategies across the groundnut supply chain.

2023-01-01, S., Srivatsa Srinivas, Marathe, Rahul R.

With the advent of COVID-19, urban transportation has been severely disrupted. We develop a stylized analytical model to study the effect of COVID-19 on the optimal pricing and hygiene level decisions of e-hailing taxi services, which play a crucial role in urban transportation. We analyze whether autonomous vehicles can aid the e-hailing taxi firms to sustain operations during these troubled times. In particular, we provide conditions under which the e-hailing taxi firms should collaborate with an original equipment manufacturer to introduce autonomous vehicles for urban transportation. Owing to the high fixed cost associated with acquiring autonomous vehicles, the e-hailing taxi firms intend to collaborate with an original equipment manufacturer. If the e-hailing taxi firm obtains a significant share from each ride in its collaboration, the hygiene level with autonomous vehicles is always greater than the hygiene level without autonomous vehicles, which is vital during the pandemic. With respect to the question of whether the e-hailing taxi firm should collaborate with the original equipment manufacturer to introduce autonomous vehicles from consumers’ viewpoint, we surprisingly find that the consumers are better off when the autonomous vehicles are introduced without collaboration both in the short-run and the long-run. However, given the high fixed cost of introducing autonomous vehicles, the e-hailing taxi firm will find it profitable to collaborate with an original equipment manufacturer if and only if its share from each ride is significant enough.