A demo of a nurse scheduling model
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Updated
May 12, 2024 - Python
A demo of a nurse scheduling model
Determine where to place new charging stations on a map based on locations of existing charging stations and points of interest.
Solve different formulations of the portfolio optimization problem.
Use a hybrid solver to use the minimum number of bins to pack items with different dimensions
Implementation of knapsack problem, set up for scaling to large problem size
Group satellites into constellations such that their average observation coverage is maximized
Solve a Sudoku puzzle with a quantum computer
Schedule employees using a constrained quadratic model with a hybrid solver.
Solve the Vehicle Routing Problem (and its variants) using a hybrid solver and Qbsolv.
Finds optimal crop rotations for a set of crops to be planted in a connected set of plots using the LeapHybridDQMSampler.
Finds the optimal stem configuration of an RNA sequence using the LeapHybridCQMSampler.
Use a hybrid solver to select features from two data sets
Find the minimal number of immunization doses required to break the transmission cycle of a virus or infectious disease within a population. Solved using the LeapHybridCQMSampler.
A demo of graph coloring using Leap's hybrid constrained quadratic model (CQM) solver.
Manage water levels in a reservoir by controlling water pumps.
Minimize messaging between computers in a distributed computing system by using the LeapHybridCQMSampler. This problem is also known as the graph k-partitioning problem.
Determine a schedule for running a set of jobs on a certain number of machines using the LeapHybridCQMSampler.
Perform basic image segmentation using discrete quadratic models (DQM) and hybrid solvers.
Demonstrates how to formulate the n-queens problem as a QUBO, which we then solve using Leap’s hybrid solvers.
Solve cryptarithmetic addition puzzles using the LeapHybridCQMSampler.
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