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The GA Procedure
The GA Procedure
Overview: GA Procedure
Getting Started: GA Procedure
Initializing the Problem Data
Choosing the Problem Encoding
Setting the Objective Function
Controlling the Selection Process
Setting Crossover Parameters
Setting Mutation Parameters
Creating the Initial Generation
Monitoring Progress and Reporting Results
A Simple Example
Syntax: GA Procedure
PROC GA Statement
ContinueFor Call
Cross Call
Dynamic_array Call
EvaluateLC Call
GetDimensions Call
GetObjValues Call
GetSolutions Call
Initialize Call
MarkPareto Call
Mutate Call
Objective Function
PackBits Call
Programming Statements
ReadChild Call
ReadCompare Call
ReadMember Call
ReadParent Call
ReEvaluate Call
SetBounds Call
SetCompareRoutine Call
SetCross Call
SetCrossProb Call
SetCrossRoutine Call
SetElite Call
SetEncoding Call
SetFinalize Call
SetMut Call
SetMutProb Call
SetMutRoutine Call
SetObj Call
SetObjFunc Call
SetProperty Call
SetSel Call
SetUpdateRoutine Call
ShellSort Call
Shuffle Call
UnpackBits Function
UpdateSolutions Call
WriteChild Call
WriteMember Call
Details: GA Procedure
Using Multisegment Encoding
Using Standard Genetic Operators and Objective Functions
Defining a User Fitness Comparison Routine
Defining User Genetic Operators
Defining a User Update Routine
Defining an Objective Function
Defining a User Initialization Routine
Specifying the Selection Strategy
Incorporating Heuristics and Local Optimizations
Handling Constraints
Optimizing Multiple Objectives
Examples: GA Procedure
Traveling Salesman Problem with Local Optimization
Nonlinear Objective with Constraints Using Repair Mechanism
Quadratic Objective with Linear Constraints, Using Bicriteria Approach
References
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