In this paper, we present an approach for measuring certain properties of synthetic optimization problems based on the assumed distribution of coefficient values. We show how to estimate the proportion of all possible solutions that are feasible for the 0-1 Knapsack Problem. We calculate the population variance of the possible solution values and assess the impact of objective-constraint correlation on the variability of feasible solution values. We also show how inter-constraint correlation affects the proportion of feasible solutions in the 2-dimensional Knapsack Problem. Finally, we discuss the significance of our findings for designers of computational experiments.
Charles H. Reilly