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Placement Algorithms

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Genetic Algorithm : ... schema . : ... – PowerPoint PPT presentation

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Date added: 13 February 2019
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Title: Placement Algorithms


1
Placement Algorithms
2
Genetic Algorithm
  • ????? ????? ??????? ?? ????.
  • ???? ???? Gate Array Placement
  • ???? ?? ?? ?????? placement??? ????? (???????)
    ?????
  • ?? placement ???? ?? ???. (8,3,2,5,1,7,4,6,9)
  • ?????? ???? (mi, xi, yi)
  • ???? ?? ?? ???? schema (-,-,2,5,1,7,-,-,-)
  • ????? ????? ???????? ?? ???.

3
Genetic Algorithm
  • ?? ?? ??? ????? ????? ?? ???? fitness???
    (??????? ?? ????) ?? ????? placement ?? ???? ??
    ??? ??????? ?? ????.

4
Genetic Algorithm
  • ?? ?? ??? ????? ????? ?? ???? fitness???
    (??????? ?? ????) ?? ????? placement ?? ???? ??
    ??? ??????? ?? ????.
  • ?? ??? ?? ????? ?????? ?????? ?? ????.
  • ????? cross-over? mutation ?? ????? ?????? ??
    ????? ?? ????/ ????? ??? ?? ????? ?? ????.
  • ??????? ???????
  • ????? ??? ???? ???? ??????? ? ???? ?? ????? ???
    ??? (????? ????).
  • ???????? ????? ???? ????? ?? fitness ???? ??
    ?????? ??? ? ????? ???.

5
????? ????? ?? Gate Array Placement
  • Cross-over ????? ?? schema ?? ?? ????.
  • ???? ?????? ?? ???? ?????? ? ????? ?? ???? ??
    ?? ??.
  • ????? ????? ???? ? ????? ???? ????.
  • ??? crossover
  • ????? ?????? BFS ?? ????? DFS ?? ????? ?? ???

6
????? ????? ?? Gate Array Placement
  • Mutation ????? ???? ????? ??? ??? ????
    ???????? ?? ????? ??????? ????? ?? ??? ? ??????
    ?? ?? ??? ????? ????? ?????? ??????? ????? ????.
  • ?? ?????? ????? ????? ????? ??? ? ?? ????? ??
    ?????? ???? ?? ??? ????.
  • ???? pairwise interchange
  • ??? ???

7
??????
  • ?????? ????? ???? ??????
  • ?????? ?????? ??? ????? ??? ???? ? ???? ?????
    ???? ? ????? ?? fitness ????? ?????? ????.
    ??????
  • ?????? ?????? ??????
  • ????? ??? ?? ????? ?? fitness ?????? ?? ??????
    ?????? ?????? ????.

8
????????
Alg Genetic noPop SIZE_POP noMutate
noPop P? noOffspring noPop P? pop
CONSTRUCT_POP (noPop) for (i1 to noPop)
SCORE (pop(i)) for (i1 to
noGeneration) for (j1 to
noOffspring) (x,y)
CHOOSE_PARENT(pop) offspring(j)
GENERATE (x,y) SCORE(offspring(j))
pop SELECT (pop, offspring,
noPop) for (j1 to noMutate)
Mutate(pop) return highest
scoring individual in population
9
Two More Crossover Operations
  • Cut-and-paste Chain moves
  • Copy a randomly selected cell e and its four
    neighbors from parent 1 to a copy of parent 2.
  • The cells that earlier occupied the neighboring
    locations in parent 2 are shifted outwards.

10
Two More Crossover Operations
  • Cut-and-paste Swapping
  • Copy k ? k square modules from parent 1 to a copy
    of parent 2 (k random from a normal
    distribution with mean 3 and variance 1).
  • Before copying, swap the cells not in both square
    modules with those repeated outside the square.

11
Inversion
bidefgcha ? bidhcgfea.
b
i
d
e
f
g
c
h
a
12
Score
  • ?? ???? cost ?? ?????? ?? ???.
  • ???????? ??? ?? ?? ???? ?? ????? ?????.

13
Simulation-Based Algorithms
  • G.A. ????? ?? ???? ?? ???? ??? SA ?? ?? ???? ???
    ?? (?? ???) ???? ?? ????.
  • ? ?? SA ?? ???? ??? ???? ??? ?? ????? ?? ??? ????
    ? ?????? ???.
  • GA ???? ?? ????? ????.
  • FD ???? ??? ????? ?????? ????.
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