2-D cutting stock problem
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Hello, I've been trying to help my bro for his glass business, but with not much success. The problem I need to solve is that he needs optimum solution to cut a defined big glass sheet into specified equal shorter pieces. This is a simple 2-D cutting stock problem. Like if big sheet size is 10x6, and small sheets size is 2x1, what are the maximum small sheets he can get out of the big one. My objective: To make a small application that would take length and width of of big sheet, small sheets, and number of small sheets as input and should show how to cut the sheets and total wastage as output. Can anybody help me in this regard? Some links or some help in making an algo for this kind of problem would do. Thanks, Ammar There is a difference in knowing the path and walking the path.
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Hello, I've been trying to help my bro for his glass business, but with not much success. The problem I need to solve is that he needs optimum solution to cut a defined big glass sheet into specified equal shorter pieces. This is a simple 2-D cutting stock problem. Like if big sheet size is 10x6, and small sheets size is 2x1, what are the maximum small sheets he can get out of the big one. My objective: To make a small application that would take length and width of of big sheet, small sheets, and number of small sheets as input and should show how to cut the sheets and total wastage as output. Can anybody help me in this regard? Some links or some help in making an algo for this kind of problem would do. Thanks, Ammar There is a difference in knowing the path and walking the path.
I worked on a similar type algorithm several yrs ago fro abt 6months for Aluminium joinery extrusion, the wastage was reduced considerably. For a small production run, I would be lazy and use a TSP nodes style way of testing various combinations. For a larger productions run I would use a linear programming engine to get a local solution. If the sizes were standard 2x1 all the way I would represent them as binary constraints. Regardz Colin J Davies
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Hello, I've been trying to help my bro for his glass business, but with not much success. The problem I need to solve is that he needs optimum solution to cut a defined big glass sheet into specified equal shorter pieces. This is a simple 2-D cutting stock problem. Like if big sheet size is 10x6, and small sheets size is 2x1, what are the maximum small sheets he can get out of the big one. My objective: To make a small application that would take length and width of of big sheet, small sheets, and number of small sheets as input and should show how to cut the sheets and total wastage as output. Can anybody help me in this regard? Some links or some help in making an algo for this kind of problem would do. Thanks, Ammar There is a difference in knowing the path and walking the path.
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Hello, I've been trying to help my bro for his glass business, but with not much success. The problem I need to solve is that he needs optimum solution to cut a defined big glass sheet into specified equal shorter pieces. This is a simple 2-D cutting stock problem. Like if big sheet size is 10x6, and small sheets size is 2x1, what are the maximum small sheets he can get out of the big one. My objective: To make a small application that would take length and width of of big sheet, small sheets, and number of small sheets as input and should show how to cut the sheets and total wastage as output. Can anybody help me in this regard? Some links or some help in making an algo for this kind of problem would do. Thanks, Ammar There is a difference in knowing the path and walking the path.
My best advise for your brother is: forget about a custom program and buy a packaged one. You would need a lot of programming (and operational research) man.years to get something robust enough and for sure not optimum. A lot of possible solution techniques, probably combined: 1-dynamic programming 2-integer programming 3-simulated annealing 4-genetic programming 5-heuristics a gogo... Life is too short ;-) Maurho
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My best advise for your brother is: forget about a custom program and buy a packaged one. You would need a lot of programming (and operational research) man.years to get something robust enough and for sure not optimum. A lot of possible solution techniques, probably combined: 1-dynamic programming 2-integer programming 3-simulated annealing 4-genetic programming 5-heuristics a gogo... Life is too short ;-) Maurho
Maurho wrote: forget about a custom program and buy a packaged one I agree. This[^] seems suitable :-) -- Ian Darling "The moral of the story is that with a contrived example, you can prove anything." - Joel Spolsky
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Maurho wrote: forget about a custom program and buy a packaged one I agree. This[^] seems suitable :-) -- Ian Darling "The moral of the story is that with a contrived example, you can prove anything." - Joel Spolsky