Application of Genetic Algorithm in Multi-objective Optimization

3.2.1.3. Continuous Method…………………………………………. 50
3.2.1.3.1. GA Operator……………………………………………. 51
3.2.1.3.2. GA Parameter…………………………………………… 52
3.3. Introducing Physical Discontinuity on the Structure and Applying Penalty
Functions……………………………………………………….
3.3.1. Flat Penalty………………………………………………………….. 54
52
3.3.2. Linear Penalty………………………………………………………. 55
3.3.3. Non-linear Penalty…………………………………………………... 55
3.4. Developing Coding Algorithm to Handle Constraints in Genetic
Algorithms……………………………………………………………....
4. Results & Discussion…………………………………………………………… 57
56
4.1. Unconstrained Problem………………………………………………… 57
4.1.1. Implementation of the Continuous Method……..………….………. 57
4.1.2. Normalized Objective Function…………….…………….……..…. 58
4.1.3. Discretized Method…………………………………….. 60
4.1.3.1. Objective Function………………………………………. 62
4.1.3.2. GA Operators for Discretized Method…………………... 62
4.1.3.3. GA Parameter…………………………………………… 63
4.1.4. Implementation of the Discretized Method……………… 63
4.2. Constrained Problem………………………………………………….. 68
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