Genetic algorithm: Difference between revisions
No edit summary |
|||
| Line 9: | Line 9: | ||
The Genetic Algorithm was first introduced by John H. Holland | The Genetic Algorithm was first introduced by John H. Holland | ||
<ref> Holland, J. H. (1973). Genetic algorithms and the optimal allocation of trials. SIAM Journal on Computing, 2(2), 88–105 </ref> | <ref> Holland, J. H. (1973). Genetic algorithms and the optimal allocation of trials. SIAM Journal on Computing, 2(2), 88–105 </ref> | ||
in 1973. It is an optimization technique based on Charles Darwin’s theory of evolution by natural selection. | |||
Before diving into the algorithm, here are definitions of the basic terminologies. | |||
* Gene: The smallest unit that makes up the chromosome (decision variable) | |||
* Chromosome: A group of genes, where each chromosome represents a solution (potential solution) | |||
* Population: A group of chromosomes (a group of potential solutions) | |||
GA involves the following seven steps: | |||
# Initialization | |||
# Evaluation | |||
# Selection | |||
# Crossover | |||
# Mutation | |||
# Insertion | |||
# Repeat 2-6 until a stopping criteria is met<br /> | |||
== Numerical Example == | == Numerical Example == | ||
Revision as of 21:00, 12 December 2024
Author: Yunchen Huo (yh2244), Ran Yi (ry357), Yanni Xie (yx682), Changlin Huang (ch2269), Jingyao Tong (jt887) (ChemE 6800 Fall 2024)
Stewards: Nathan Preuss, Wei-Han Chen, Tianqi Xiao, Guoqing Hu
Introduction
Algorithm Discussion
The Genetic Algorithm was first introduced by John H. Holland [1] in 1973. It is an optimization technique based on Charles Darwin’s theory of evolution by natural selection.
Before diving into the algorithm, here are definitions of the basic terminologies.
- Gene: The smallest unit that makes up the chromosome (decision variable)
- Chromosome: A group of genes, where each chromosome represents a solution (potential solution)
- Population: A group of chromosomes (a group of potential solutions)
GA involves the following seven steps:
- Initialization
- Evaluation
- Selection
- Crossover
- Mutation
- Insertion
- Repeat 2-6 until a stopping criteria is met
Numerical Example
1. Simple Example
We aim to maximize , where . Chromosomes are encoded as 5-bit binary strings since the binary format of the maximum value 31 is 11111.
1.1 Initialization (Generation 0)
The initial population is randomly generated:
| Chromosome (Binary) | x (Decimal) |
|---|---|
| 10010 | 18 |
| 00111 | 7 |
| 11001 | 25 |
| 01001 | 9 |
1.2 Generation 1
1.2.1 Evaluation
Calculate the fitness values:
| Chromosome | ||
|---|---|---|
| 10010 | 18 | 324 |
| 00111 | 7 | 49 |
| 11001 | 25 | 625 |
| 01001 | 9 | 81 |
1.2.2 Selection
Use roulette wheel selection to choose parents for crossover. Selection probabilities are calculated as:
Thus,
Total Fitness
Compute the selection probabilities:
| Chromosome | Selection Probability | |
|---|---|---|
| 10010 | ||
| 00111 | ||
| 11001 | Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 625} | Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \frac{625}{1,079} \approx 0.5792} |
| 01001 | Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 81} | Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \frac{81}{1,079} \approx 0.0751} |
Cumulative probabilities:
| Chromosome | Cumulative Probability |
|---|---|
| 10010 | Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 0.3003} |
| 00111 | Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 0.3003 + 0.0454 = 0.3457} |
| 11001 | Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 0.3457 + 0.5792 = 0.9249} |
| 01001 | Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 0.9249 + 0.0751 = 1.0000} |
Random numbers for selection:
Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle r_1 = 0.32, \quad r_2 = 0.60, \quad r_3 = 0.85, \quad r_4 = 0.10}
Selected parents:
- Pair 1: 00111 and 11001
- Pair 2: 11001 and 10010
3. Crossover
Crossover probability: Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle P_c = 0.7}
Pair 1: Crossover occurs at position 2.
- Parent 1: Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 00|111}
- Parent 2: Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 11|001}
- Children: Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 00001 \ (x = 1)} , Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 11111 \ (x = 31)}
Pair 2: No crossover.
- Children: Child 3: Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 11001 \ (x = 25)} , Child 4: Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle 10010 \ (x = 18)}
References
- ↑ Holland, J. H. (1973). Genetic algorithms and the optimal allocation of trials. SIAM Journal on Computing, 2(2), 88–105