Annealing Machine Optimization Device Solving Multiple Combinatorial Problems

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Solution Overview

Problem

Conventional methods for solving multiple combinatorial optimization problems sequentially result in lengthy calculation times, as each problem must be individually solved, making it inefficient to address real-world applications that require timely solutions.

Innovation Solution

An optimization device and method that assigns specific bits to each combinatorial optimization problem and sets interactions between bits to zero, allowing for simultaneous solution of multiple problems using an annealing machine, thereby reducing calculation time.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If multiple combinatorial optimization problems are solved sequentially using conventional methods, then each problem can be solved individually, but the total calculation time becomes excessively long

Engineering Contradiction:
Improvenumber of problems solved per unit timeVSAvoidtotal calculation time
Core Design Contradiction:
ProductivityVSLoss of time

Solution Approach 1:

The patent combines multiple separate combinatorial optimization problems into a single unified problem by merging their respective objective functions and constraints. This allows the annealing machine to solve all problems simultaneously in one calculation process, transforming N separate sequential calculations into one parallel calculation, thereby dramatically reducing total computation time.

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The patent creates a universal optimization framework that can handle multiple different combinatorial optimization problems within a single unified model. By formulating a general-purpose objective function that encompasses multiple specific problems, the system achieves multi-functionality, allowing one annealing calculation to address various optimization tasks that would otherwise require separate dedicated calculations.

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Measurement precision

If separate calculations are performed for each combinatorial optimization problem, then accurate individual solutions can be obtained, but the calculation process must be repeated for each problem

Engineering Contradiction:
Improvesolution accuracyVSAvoidefficiency of solving multiple problems
Core Design Contradiction:
Measurement precisionVSProductivity

Solution Approach 1:

The patent merges multiple objective functions into a single combined objective function that preserves the essential characteristics of each individual problem. By carefully constructing this unified function, the system maintains solution accuracy for each specific optimization problem while enabling simultaneous solution of all problems through a single annealing calculation process.

Inventive Principle:
Principle #5Merging (Combining)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach significantly reduces the overall calculation time for solving multiple combinatorial optimization problems, achieving efficient solutions in a fraction of the time required by conventional methods.

Implementation Method 1

a technology of performing calculation by an annealing method using an annealing machine or the like has been proposed

Methodology Applied
Scientific EffectAnnealing: Annealing

Data Source

PatentEP3862870A1Optimization device, optimization program, and optimization method
Publication Date: 2021.08.11 FUJITSU LTD
  • EP3862870A1 patent drawingFigure 1
  • EP3862870A1 patent drawingFigure 2
  • EP3862870A1 patent drawingFigure 3

AI summary

An optimization device includes a solution unit. The solution unit configured to, among a plurality of bits for solving a plurality of combinatorial optimization problems, assign a plurality of first bits to a first combinatorial optimization problem included in the plurality of combinatorial optimization problems and assign a plurality of second bits to a second combinatorial optimization problem included in the plurality of combinatorial optimization problems. The solution unit further configured to set an interaction between each of the plurality of first bits and each of the plurality of second bits to zero, and to solve the plurality of combinatorial optimization problems.