The problem contains a set of foods, which are the modeling variables; a set of nutritional requirements to be satisfied, which are the constraints; and an objective of minimizing the total cost of the food. There are two ways of looking at this problem:
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The problem can be modeled by rows, by entering the variables first and then adding the constraints on the variables and the objective function.
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The problem can be modeled by columns, by constructing a series of empty constraints and then inserting the variables into the constraints and the objective function.
Concert Technology is equally suited for both kinds of modeling; in fact, you can even mix both approaches in the same program. If a new food product is created, you can create a new variable for it regardless of how the model was originally built. Similarly, if a new nutrient is discovered, you can add a new constraint for it.