Effective traffic incident management is essential for ensuring safety, minimizing congestion, and reducing response times in emergency situations. Traditional highway incident management relies heavily on radio room operators, who must make rapid, informed decisions in high-stakes environments. This paper proposes an innovative solution to support and enhance these decisions by integrating Large Language Models (LLMs) into a decision-support system for traffic incident management. We introduce two approaches: (1) an LLM + Optimization hybrid that leverages both the flexibility of natural language interaction and the robustness of optimization techniques, and (2) a Full LLM approach that autonomously generates decisions using only LLM capabilities. We tested our solutions using historical event data from Autostrade per l'Italia. Experimental results indicate that while both approaches show promise, the LLM + Optimization solution demonstrates superior reliability, making it particularly suited to critical applications where consistency and accuracy are paramount. This research highlights the potential for LLMs to transform highway incident management by enabling accessible, data-driven decision-making support.

With the addition of Qatar Airways Cargo, the world's largest international air cargo provider, PROS is a market-leader, powering nearly 40% of the top air cargo providers. Together, PROS Smart Price Optimization and Management and PROS Smart Configure Price Quote deliver impactful results to air cargo customers--up to 3% profit improvement and up to 5% win rate improvement--by optimizing prices across online platforms in real-time, providing enhanced customer experiences and driving profitable growth. PROS market expertise is an advantage for air cargo companies as the industry continues to face disruption with volatile and often unpredictable supply and demand patterns across the global network. The industry is undergoing a digital disruption, with online platform providers making digital distribution and self-service essential to compete. With PROS, air cargo companies can optimize all sides of the margin equation, embedding real-time strategies, market data, performance insights and leveraging PROS AI – all seamlessly integrated into the sales ecosystem to deliver real-time, omnichannel quotes designed to maximize profits and provide a competitive advantage.

Note: This is the third of a five-part series covering Kubernetes resource management and optimization. In this article, we explain how machine learning can be used to manage Kubernetes resources efficiently. Previous articles explained Kubernetes resource types and requests and limits. As Kubernetes has become the de-facto standard for application container orchestration, it has also raised vital questions about optimization strategies and best practices. One of the reasons organizations adopt Kubernetes is to improve efficiency, even while scaling up and down to accommodate changing workloads.

Keelvar, a global pioneer of intelligent sourcing and automation solutions, announced it has raised $24 million in Series B funding to simplify and radically improve procurement, the world's most inefficient trillion-dollar marketplace. Keelvar's sourcing technology – which leverages AI, data science and smart sourcing bots that run on autopilot – empowers customers to make crucial supply chain decisions quickly and confidently amidst ongoing change and disruption. Costs are out of control, capacity is scarce and disruptions are everywhere. This dynamic makes it incredibly difficult for buyers and suppliers to remain agile, manage risk and strike deals" The investment – which brings Keelvar's total capital raised to $43 million – was led by 83North. Series A investors Elephant, Mosaic and Paua doubled down on their investment. Bastian Nomichacher, the co-founder and co-CEO of Celonis, also joined as a minority investor. Keelvar's Series B builds off a period of rapid growth and expansion for the company, which increased its headcount by 200% since the start of 2021 and grew ARR by 113% last year. Costs are out of control, capacity is scarce and disruptions are everywhere. This dynamic makes it incredibly difficult for buyers and suppliers to remain agile, manage risk and strike deals," said Alan Holland, founder and CEO of Keelvar.

SEATTLE, February 11, 2015 – Optimum Energy, the leading provider of data-driven cooling and heating optimization solutions for enterprise facilities, today introduced OptiCxTM Dynamic Sequencing, a software optimization tool that learns how chillers perform over time in a variety of operating conditions, and uses this data to improve the overall plant efficiency by determining the most efficient chiller to run. "The OptiCx Platform is an award-winning approach with a growing base of committed customers, and now, with Dynamic Sequencing, it's taking a big step forward," said Ian Dempster, Optimum Energy's Senior Director of Product Innovation. "When combined with OptimumLOOP, this is the most powerful chiller optimization solution available, offering substantial reductions in energy and water use." Available as an add-on for customers with a subscription to the OptiCx PlatformTM, Dynamic Sequencing works in conjunction with OptimumLOOPTM, an operational module in the OptiCx Platform. OptimumLOOP uses relational control algorithms to determine operating setpoints and parameters to turn on or off an additional chiller in a plant.