Initial performance comparisons for the delta coding algorithm

Abstract

Delta coding is an iterative genetic search strategy that sustains search by periodically re-initializing the population. This helps to avoid premature convergence during genetic search. Delta coding also remaps hyperspace with each iteration in an attempt to locate "easier" search spaces with respect to genetic search. Here, the optimization ability of delta coding is compared against the CHC genetic algorithm and a mutation driven stochastic hill-climbing algorithm on a suite of standard genetic algorithm test functions.<>