parallel simulated annealing with adaptive neighborhood determined by ga l.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Parallel Simulated Annealing with Adaptive Neighborhood determined by GA PowerPoint Presentation
Download Presentation
Parallel Simulated Annealing with Adaptive Neighborhood determined by GA

Loading in 2 Seconds...

play fullscreen
1 / 20

Parallel Simulated Annealing with Adaptive Neighborhood determined by GA - PowerPoint PPT Presentation


  • 341 Views
  • Uploaded on

Parallel Simulated Annealing with Adaptive Neighborhood determined by GA Doshisha University, Kyoto, Japan Mitsunori MIKI Tomoyuki HIROYASU ○ Toshihiko FUSHIMI Introduction Optimization problems become more complicated and larger. Heuristic search Simulated Annealing (SA)

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

Parallel Simulated Annealing with Adaptive Neighborhood determined by GA


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
parallel simulated annealing with adaptive neighborhood determined by ga

Parallel Simulated Annealing with Adaptive Neighborhood determined by GA

Doshisha University, Kyoto, Japan

Mitsunori MIKI

Tomoyuki HIROYASU

○ Toshihiko FUSHIMI

introduction
Introduction
  • Optimization problems become more complicated

and larger.

  • Heuristic search
  • Simulated Annealing (SA)

based on the simulation of the physical process “annealing”.

  • GA, CA, NN etc.

Important matters

  • Parallelization
  • Adaptive parameter tuning
algorithm of simulated annealing
Algorithm of Simulated Annealing

high

Algorithm

Energy

1. Generation

2. Judge Transition

low

Design space

Metropolis probability

3. Cooling

good acceptance

1

-⊿E

Temperature

bad acceptance

Exp( )

(⊿E = Enext - Enow)

neighborhood range
Neighborhood range

The neighborhood range in the continuous Euclid space is the extent for generating next solution.

  • Too large neighborhood range
  • Can’t search optimum effectively.
  • The range has to be small.
  • Too small neighborhood range
  • Often trapped in a local minimum.

Global optimum

  • The range has to be large.
background
Background

For the control of the neighborhood range, some method are proposed.

  • The adaptive neighborhood mechanism. [Corana 1987]
  • The advanced adaptive neighborhood mechanism. [Miki 2002]

These methods control the neighborhood range using an appropriate acceptance ratio.

This type of adaptive neighborhood method is very effective and useful, but the target acceptance ratio should be determined experimentally.

Propose a new adaptive neighborhood mechanism

purpose
Purpose

Controlling the neighborhood range adaptively during the search.

Parallel Simulated Annealing with Adaptive Neighborhood

determined by Genetic Algorithm (PSA/ANGA)

Characteristics

  • This method is Parallel model.
  • This method parallels neighborhood ranges on each processes.
  • This neighborhood range is controlled by GA.
effect of neighborhood ranges
Effect of Neighborhood Ranges
  • The neighborhood range has a significant effect on the accuracy of the solution.
  • In order to verify this effect, some numerical experiments were carried out with various fixed neighborhood ranges.

Fixed neighborhood range

Search space

large

Compare the qualities of the solutions.

Neighborhood range

Obtain the effect of the neighborhood ranges.

small

test problems
Test problems

Rastrigin function

Mathematical

test functions

Griewangk function

Rosenbrock function

Rastrigin

Griewangk

Rosenbrock

appropriate neighborhood range
Appropriate neighborhood range

The neighborhood range has a significant effect on the performance of SA.

Rastrigin

Appropriate

neighborhood range

Good solution

appropriate neighborhood range10
Appropriate neighborhood range

The neighborhood range has a significant effect on the performance of SA.

Appropriate

neighborhood range

Griewangk

Good solution

appropriate neighborhood range11
Appropriate neighborhood range

The neighborhood range has a significant effect on the performance of SA.

Appropriate

neighborhood range

Rosenbrock

Good solution

concept of psa anga
Concept of PSA/ANGA

There are the appropriate neighborhood ranges in SA when solving the continuous optimization problems.

  • The appropriate neighborhood ranges depend on problems.
  • It is difficult to find the appropriate neighborhood ranges in advance.

PSA searches the solution with various neighborhood range.

The neighborhood range determined adaptively by GA.

Parallel Simulated Annealing with Adaptive Neighborhood

determined by Genetic Algorithm (PSA/ANGA)

algorithms of psa anga
Algorithms of PSA/ANGA

1

Fitness =

Energy

Multiple SA processes searches the solution with various neighborhood range.

GA operators are applied on neighborhood ranges.

large

Neighborhood range

small

abstract of numerical experiments
Abstract of numerical experiments

PSA/ANGA is compared with a parallel SA with optimum fixed neighborhood range, PSA/FN.

Comparative method

Optimum fixed neighborhood range

Parallel SA with Fixed Neighborhood (PSA/FN)

Use the optimum fixed neighborhood range determined by preliminary numerical experiments.

performance of the proposed method
Performance of the proposed method

Proposed method

The proposed method, PSA/ANGA, provides better performance than PSA/FN in all problems.

history of neighborhood range
History of Neighborhood range
  • History of the neighborhood ranges in 32 SA processes.
  • The appropriate neighborhood range varies dynamically during the search.

Rastrigin

The appropriate neighborhood range is automatically determined using GA.

history of energy rastrigin
History of energy (Rastrigin)
  • The proposed method, PSA/ANGA, shows fast convergence of the energy and obtains lower energy than PSA/FN.
  • Accuracy of the solution improves because the neighborhood ranges were changed adaptively.
conclusions
Conclusions

A new Parallel Simulated Annealing method with adaptive neighborhood range mechanism is proposed.

Parallel SA with Adaptive Neighborhood

determined by Genetic Algorithm (PSA/ANGA)

The appropriate neighborhood range varies according to the condition of the search.

The proposed method adapts to these appropriate neighborhood ranges.

PSA/ANGA shows good performance on the some test functions.

The method is effective in SA for continuous optimization problems.

questions and answers
questions and answers

Thank you for your kind attention.