Generating coefficients for optimization test problems with implicit correlation induction

We consider methods for inducing correlation between the objective function and constraint coefficients in 0-1 Knapsack, generalized assignment, capital budgeting, and set covering problems. Each of the methods that we examine is an implicit correlation-induction (ICI) method that has been featured in the literature. However, the correlation levels used in the corresponding computational experiments are typically neither quantified nor systematically controlled. We present closed-form expressions for the population correlation levels induced with the ICI methods to facilitate the quantification and systematic control of the correlation levels in computational experiments. We also discuss the advantages and disadvantages of ICI methods.

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