#nvidia #routing #tsp #vrp #cuopt
Привлекло внимание, что в рамках NVIDIA NIM Agent Blueprint Нвидия предлагет решение по оптимизации маршрутов. Сольвер cuOpt теперь развёрнут в облаке (видимо, по подписке).
"One of the biggest challenges in the commercial fleet industry is routing optimization. This is prevalent in many industries, where determining the most cost-effective route can contribute significant cost savings for meal delivery where a single restaurant franchise can deliver millions of meals a day, or a telecommunications company that dispatches millions of jobs per year. In these types of large scale scenarios, inefficient routes can cost billions of dollars in operational costs as well as reduce our environmental carbon footprint. A computational solver can minimize these inefficiencies by finding the most optimal routes across a list of locations. Computational CPU based solvers are available today but using the massive throughput of GPU acceleration, more ambitious algorithms will help fuel our future.
Route optimization problems such as those described above are commonly known as the Traveling Salesperson (TSP) problem. To reduce the time to develop a GPU accelerated TSP solution, NVIDIA has developed the route optimization AI workflow to streamline development of Vehicle Routing Problem (VRP) solutions."
https://docs.nvidia.com/ai-enterprise/workflows-route-optimization/0.1.0/technical-brief.html
Привлекло внимание, что в рамках NVIDIA NIM Agent Blueprint Нвидия предлагет решение по оптимизации маршрутов. Сольвер cuOpt теперь развёрнут в облаке (видимо, по подписке).
"One of the biggest challenges in the commercial fleet industry is routing optimization. This is prevalent in many industries, where determining the most cost-effective route can contribute significant cost savings for meal delivery where a single restaurant franchise can deliver millions of meals a day, or a telecommunications company that dispatches millions of jobs per year. In these types of large scale scenarios, inefficient routes can cost billions of dollars in operational costs as well as reduce our environmental carbon footprint. A computational solver can minimize these inefficiencies by finding the most optimal routes across a list of locations. Computational CPU based solvers are available today but using the massive throughput of GPU acceleration, more ambitious algorithms will help fuel our future.
Route optimization problems such as those described above are commonly known as the Traveling Salesperson (TSP) problem. To reduce the time to develop a GPU accelerated TSP solution, NVIDIA has developed the route optimization AI workflow to streamline development of Vehicle Routing Problem (VRP) solutions."
https://docs.nvidia.com/ai-enterprise/workflows-route-optimization/0.1.0/technical-brief.html
NVIDIA Docs
Technical Brief
The route optimization workflow demonstrates how to use NVIDIA cuOpt to minimize vehicle routing inefficiencies by finding the most optimal route for a fleet of vehicles making deliveries, pickups, dispatching jobs, etc.