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I'm trying to implement a genetic algorithm for the 1-dimensional stock cutting problem. The problem is that we have unlimited stock of metal with m different length and n different order length (smaller than stock length) with different quantities have to be cut from the stock metal.

My questions are:

How to encode the chromosome? (they have constraints like: the total cuts length has to be smaller than the stock size..)

How a crossover and mutation operator would work in this situation?

I find them would be quite different from normal operators we use for the TSP problem because there are many constraints when you wan to shuffle the population (Eg. Pieces can't be longer than the stock,...)

Hoàng Thái Khánh Côn
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  • Your question is unclear. First of all, what is "**the** 1-dimensional stock-cutting problem"? I know of several. You need to specify, including evaluation and constraints. How do you – Prune Nov 21 '17 at 17:56
  • How do you shuffle the population, and how does a long piece even get to that phase of the processing? – Prune Nov 21 '17 at 18:02
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    Look at this [solution](http://parallel.bas.bg/ESGI113/final_reports/problem3_fr.pdf). – Todor Balabanov Nov 22 '17 at 18:00

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