Operations Research is, and has always been, about solving one of the world’s toughest challenges: planning problems. Finding the best way to allocate resources, schedule shifts, or route deliveries under an abundance of real-world constraints. It is widely accepted that optimizing those problems will make the world a better place. The value has never been in question. But the road to real-world adoption? That’s been another story. With PlanningAI, we can alter the narrative.
PlanningAI intentionally captures scheduling, routing, and strategy because businesses naturally function across multiple timeframes and complexities. Find out more about the etymology of PlanningAI in this blog post.
Generative AI might be grabbing the headlines, but on the opposite end of the AI spectrum there’s a complex subset that’s been driving solutions long before the buzz began: PlanningAI. In this blog post, we’ll explain how PlanningAI en GenAI are fundamentally different, despite being both AI.
LLMs have come a long way in recently, but they still struggle with complex planning, however, there’s an older form of AI that handles complex planning…
In 2022, Geoffrey thought his life’s work was over. Almost 2 decades of innovation seemed lost. Today, the world-class technology that once seemed lost is thriving under a new name, Timefold. Find out how the tables turned in this compelling blog post.
Discover how you can use Timefold Solver, our Open Source AI library, to optimize Santa’s travel route. Leave no gift un-gifted!
Discover the techniques Timefold Engineers deploy to make your Python code faster.
