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Linear programming is often a mathematical procedure for optimizing methods. Primarily, this includes maximizing an aim functionality when adhering to specified constraints.
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This issue can be solved with simpler approaches, but is solved in this article with the Big M process as a demonstration of the best way to offer with differing kinds of constraints with the large M approach.
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All other better lines usually do not pass through the possible region. All other lower strains pass through multiple point in the possible area, and do not optimize the (y)-intercept of the line.
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Besides these constraints, You can find also several "typical sense" constraints. It's impossible to create a lot less than 0 of any aspect, so these constraints will also be created:
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