遗传算法。群体包含不执行条件的染色体。我该怎么办？ [英] Genetic algorithm. A population contains chromosomes, that don't perform conditions. What should I do with?
问题描述
我正在使用遗传算法研究运输推销员问题解决方案。
有些染色体包含最短路径，但它们仍然不合适。例如，推销员必须在下午6点到达A市，但是使用染色体的解决方案，他将在晚上7点到达那里。因此，这个解决方案是不正确的。
我应该怎么处理这个问题？
首先，我可以改变这些染色体。但是我怎么能这样做呢？
其次，我可以保留它们。那我该怎么做呢？
第三，我可以替换它们，但我不知道应该用什么代替。
你能帮帮我或者推荐一些有用的信息吗？
英语不是我的母语，如果我说错了就很抱歉。
这是你想要的问题处理GA模型中的各种约束。可以有两种类型的约束：
1.硬约束：必须满足的要求。您可以通过编排突变来丢弃此类解决方案或进行修复。
2.软约束：可以违反的要求。您可以采用措施惩罚健身功能中的此类解决方案，使其不利于后续选择。
了解更多：
1. 处理遗传算法中的约束 [ ^ ]
2。 遗传算法揭秘 [ ^ ]
3. 遗传算法实现 [ ^ ]
I'm working on Transport Salesman Problem solution with a Genetic Algorithm.
Some chromosomes are contain the shortest way, but they still aren't appropriate. For example, a salesman must get to the A city at 6.00 pm, but using the solution of a chromosome he'll get there at 7.00 pm. Thus, this solution is not correct.
What should I do with this issue?
Firstly, I can change these chromosomes. But how can I do it?
Secondly, I can keep them. How should I do the selection then?
Thirdly, I can replace them, but I have no idea what should I use instead.
Could you please help me or recommend me some useful information?
English is not my native language, so sorry if I said something wrong.
It is a matter of how you want to handle the various constraints in your GA model. There can be 2 types of constraints:
1. Hard Constraints: Requirements that must be met. You may discard such solutions or repair them by orchestrating a mutation.
2. Soft Constraints: Requirements that can be violated. You may introduce measures to penalize such solutions in the fitness function to make them less favorable for subsequent selections.
Find out more :
1. handling constraints in genetic algorithms[^]
2. Genetic Algorithms Demystified[^]
3. Genetic Algorithms Implementation[^]
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