Ananth Krishnamurthy

TL;DR: In this article, the authors investigate the performance impact of vehicle assignment and configuration decisions on the performance of a multi-class semi-open queuing network with class switching in an autonomous vehicle-based storage and retrieval system.

TL;DR: In this article, the authors model variants of the two systems as an open queuing network (OQN) and use an existing tool for the analysis of OQNs, called the manufacturing system performance analyser (MPA), for analysing the performance of the AS/RS and AVS/RS.

TL;DR: A simulation based experimental design for automated unit-load storage and retrieval systems based on autonomous vehicle technology to identify factors affecting their performance shows that there is three-way interaction effect on each response at a 95% confidence level.

TL;DR: In this article, the authors address the problem of designing supply chains that are resilient to natural or human-induced extreme events, focusing on the development of efficient restoration strategies that aid the supply chain in recovering from a disruption, thereby limiting the impact on its customers.

TL;DR: This paper model the autonomous vehicle storage and retrieval system (AVS/RS) as a semi-open queuing network (SOQN) and apply a matrix-geometric method (MGM) for analyzing it and solves the network using the MGM and obtain its key performance measures.