Virtus AllianzGI Artificial Intelligence & Technology Opportunities Fund (NYSE: AIO), a diversified closed-end fund, today announced that it will institute a managed distribution plan effective with the distribution payable February 1, 2022. Coincident with the adoption of the plan, the Fund will raise its monthly distribution to $0.15 per share, a 20% increase from the distribution of $0.125 per share payable January 3, 2022. The increased distribution represents an annualized distribution rate of 6.7% based on the closing market price of $26.88 on December 16, 2021. The Fund is undertaking these actions as part of its ongoing efforts to enhance shareholder value by both seeking to provide a more attractive distribution rate and furthering its efforts to reduce the current discount to net asset value at which its shares currently trade. The Board also approved a change in the Fund's fiscal year end from February 28 to January 31, effective January 31, 2022.

This study focuses on the design and development of methods for generating cargo distribution plans for large-scale logistics networks. It uses data from three large logistics operators while focusing on cross border logistics operations using one large graph. The approach uses a three-step methodology to first represent the logistic infrastructure as a graph, then partition the graph into smaller size regions, and finally generate cargo distribution plans for each individual region. The initial graph representation has been extracted from regional graphs by spectral clustering and is then further used for computing the distribution plan. The approach introduces methods for each of the modelling steps. The proposed approach on using regionalization of large logistics infrastructure for generating partial plans, enables scaling to thousands of drop-off locations. Results also show that the proposed approach scales better than the state-of-the-art, while preserving the quality of the solution. Our methodology is suited to address the main challenge in transforming rigid large logistics infrastructure into dynamic, just-in-time, and point-to-point delivery-oriented logistics operations.