A simple 'for()'

[Example Model: ProductMix5 -- To open, click RASON Examples - Example Models using Arrays Loops and Tables -- Using Loop]

variables: {
     x: {
            lower: [0, 0, 0],
            finalValue: []
        }
    }, 
data: {
    	profits: {
            dimensions: [3],
            value: [75, 50, 35],
            binding: "get",
            finalValue: []
    },

parts: {
            dimensions: [5, 3],
            value: [
                [1, 1, 0],
                [1, 0, 0],
                [2, 2, 1],
                [1, 1, 0],
                [2, 1, 1]
            ]
      },

      inventory: {
            value: [450, 250, 800, 450, 600]
      }
    },

constraints: {
	"for(p in 1..5)": {
"cons[p]": { formula: "sumproduct(parts[p,], transpose(x))", upper: 'inventory' }
	}
    }

In the example above, five constraints are created in the vertical array cons[]. The constraints are defined as an array (rather than a table) because 'inventory', holding the upper bounds of the constraints, is a vertical array. Each constraint has a unique index p. To evaluate a given constraint, the model fixes p to a single value (for example, p = 1) and evaluates the formula for that index. Each constraint is evaluated independently for a fixed value of p, not as a vectorized array-formula evaluation. Note that 'x' is transposed from a vertical array to a horizontal array so it can be multiplied with the with the row of the parts array corresponding to index p (parts[p,]).