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In this tutorial, we implement real-time optimal control of traffic signals using combinatorial
optimization for ever-changing traffic conditions. We also simulate the traffic volume in the city when
such optimal control is considered.
Here, we use black-box optimization to optimize traffic signal control in a city where commercial
facilities may cause traffic congestion. We apply traffic simulation based on multi-agent simulation to
implement and demonstrate the optimization.
Fixstars Amplify is used to solve the 14 NP problems presented in the paper, A. Lucas, Front. Phys.
Optimal allocation of employees to stores is essential for retail and service industries with employees
with different skills and needs. In this tutorial, we will perform such an optimization using Fixstars
This example code deals with the CVRP, which can be applied to efficient delivery scheduling in the
industry and to optimizing the order of visits in garbage collection and street cleaning.
In this tutorial, we design the airfoil shape to maximize the lift-to-drag ratio based on fluid flow
simulations. We use
black-box optimization with a machine-learning model and simulated annealing for non-binary decision
In this tutorial, we optimize the operating condition of a chemical reactor to maximize its production.
We use black-box
optimization based on a machine-learning model and chemical reaction simulations.
Here, we demonstrate black-box optimization using machine learning and an Ising machine/quantum annealer
exploration to realize a model high-temperature superconducting material.
Black-box optimization (BBO) can be applied to complex and unknown functions. In this tutorial, we
implement BBO using machine learning and combinatorial optimization with Fixstars Amplify.
As an example of a complex QUBO formulation, we will develop an application that solves Picross, a puzzle
game in which
the user paints squares and completes a picture based on clues given by numbers.
In this tutorial, we optimize the assignment of people and cars for collective ridesharing, to minimize
traveled by each person and the number of cars.
Sudoku is a popular number-placement puzzle. Here, we learn how to formulate and implement a Sudoku
solver as a
combinatorial optimization problem.
In this tutorial, we learn the traveling salesman problem and implement a solver.
In this tutorial, we solve a graph coloring problem, where we assign colors to the vertices of a graph
This example code contains the minimal code for using all available machines
with Amplify SDK.
Here, we solve a taxi matching problem, where the cost of dispatching a taxi is minimized given multiple
multiple taxi locations.
In this tutorial, we will develop an application to solve a meeting room allocation problem based on
This tutorial describes how to impose constraints on the decision variables in Amplify SDK.
This tutorial introduces the Amplify feature to formulate objective
functions using polynomials.
Combinatorial optimization can be used for noise reduction. Here, we
will implement a combinatorial optimization solver to reduce noise in an image.
Number partitioning is a typical combinatorial optimization problem. In this tutorial, we will use
Amplify to solve a
number partitioning problem.
In this tutorial, we will learn the basics of solving combinatorial optimization problems with Amplify.
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