How to identify the individuals not satisfying non-linear inequality constraints?
조회 수: 1 (최근 30일)
이전 댓글 표시
I am using Genetic Algorithm to solve a problem which involves minimising a fitness function, subject to some non-linear inequality constraints and decision variables subject to integer constraint. I am setting Penalty as a non-linear constraint algorithm which adds a penalty to the fitness value of infeasible individual (not satisfying the constraint) depending on the constraint violation and worst feasible fitness value in that population.
I am also saving GA population history and scores during all generations. Now, I want to visualise that during each generation which individuals didn't satisfy the constraint and caused a penalty in fitness value?
I want to show whole optimisation process like individuals during 1st generation (feasible and infeasible), with corresponding fitness value and evolving to the optimum solution till last generation
댓글 수: 5
Gifari Zulkarnaen
2020년 2월 20일
If you know what are the constraints, make a constraint function, then input the individuals to get the constraint output (for knowing the infeasibility). Do you know the constraints?
답변 (0개)
참고 항목
카테고리
Help Center 및 File Exchange에서 Genetic Algorithm에 대해 자세히 알아보기
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!