1 exact and heuristics algorithms. 2 exercice1 model charging station deployement problem. program...
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Exercice1
• Model charging station deployement problem.
• Program the Genetic algorithm to solve it.
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Genetic algorithm: Chromosomes
• Chromosomes are used to code information.
• Example: 3 warehouses, 5 clients
W1 W2 W3 C1 C2 C3 C4 C5
1 0 1 3 2 1 1 2
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Genetic algorithm: OperatorsPopulationPopulation
SelectSelect
CrossoverCrossover
MutationMutation
Recombination
Recombination
Best solution
Best solution
Final iterati
on
Final iterati
on
Yes
No
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Genetic algorithm: OperatorsPopulationPopulation
SelectSelect
1- Randomly generate an initial population (random chromosomes)
3-Select some chromosomes from the population as an offspring individual:
-Randomly - using stochastic method
2 -Compute and save the fitness (Objective function F) for each individual (chromosomes) in the current population
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Genetic algorithm: Operators• The crossover is done on a selected part of
population (offspring) to create the basis of the next generation (exchange information).
• This operator is applied with propability Pc
CrossoverCrossover
W1 W2 W3 C1 C2 C3 C4 C5
1 0 1 3 2 1 1 2
W1 W2 W3 C1 C2 C3 C4 C5
1 0 1 3 2 1 1 2
Father
Mother
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Genetic algorithm: Operators
CrossoverCrossover
Child 1
Child 2
W1
W2
W3
C1 C2 C3 C4 C5
1 0 1 3 2 1 1 2
W1
W2
W3
C1 C2 C3 C4 C5
1 0 1 3 3 1 2 2
W1
W2
W3
C1 C2 C3 C4 C5
1 0 1 3 3 1 1 2
W1
W2
W3
C1 C2 C3 C4 C5
1 0 1 3 2 1 2 2
Father
Mother
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Genetic algorithm: Operators• This operation is a random change in
the population. It modifies one or• more gene values in a chromosome to
have a new chromosom value in the pool.
• This operator is applied with propability Pm
MutationMutation
W1 W2 W3 C1 C2 C3 C4 C5
1 0 1 3 2 1 1 2
W1 W2 W3 C1 C2 C3 C4 C5
0 0 1 3 2 1 1 2
Current
New
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Genetic algorithm: Operators• Recombination combines the
chromosomes from the initial population and the new offspring chromosomes.
Recombination
Recombination
Final iterati
on
Final iterati
on
• Repeat a fixed number of iteration or until the solution converge to one solution (always with the best fitness) .