[Paradiseo-help] [PEO] Multistart over an evolutionnary algorithm (Lesson 2)

Clément Perrod clement.perrod at gmail.com
Lun 27 Avr 14:34:32 CEST 2009


Hi,

I am having some troubles with lesson 2 of PEO.

I have a little network as to process my tests (only 2 computers each
with 2 nodes) and I wanted to apply the lesson 2 on my work. But as I
was testing the binary given with lesson2:
`paradiseo-1.2.1/paradiseo-peo/build/tutorial/Lesson2/multistartGA'
with the param file
`paradiseo-1.2.1/paradiseo-peo/build/tutorial/Lesson2/param' I had a
strange result.

There are 3 EA initialized but at the end only one evolved, as you can
see below:

---------------------------------------------------------------------------------------

$ mpdtrace
computer1
computer2
$ mpiexec -n 4 ./multistartGA @param
Initial Population
10
292342
296840
299884
307598
313376
316344
319514
324060
330920
338340

Initial Population
10
287828
289658
292186
293982
309568
314552
314758
320238
321284
321416

Initial Population
10
290176
293316
297572
303626
304466
306742
312322
317976
319036
337678

STOP in eoGenContinue: Reached maximum number of generations [1000/1000]
FINAL Population
10
292342
296840
299884
307598
313376
316344
319514
324060
330920
338340


Instance size = 12
Best known value in the litterature = 224416

Best solution found	292342
FINAL Population
10
290176
293316
297572
303626
304466
306742
312322
317976
319036
337678


Instance size = 12
Best known value in the litterature = 224416

Best solution found	290176
FINAL Population
10
240952
240952
240952
240952
240952
240952
240952
240952
240952
240952


Instance size = 12
Best known value in the litterature = 224416

Best solution found	240952

---------------------------------------------------------------------------------------

Is there any way I did something wrong during the launch process? Or
is there something I did not understand about this lesson?

Thank you for your help,

Sincerely,

-- 
Clément Perrod
EPITA 2009
Stagiaire EURODECISION
Operational Research - Resources Optimisation




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