Further Experimentations On The Scalability Of The GEMGA

. This paper reports the recent developments of the Gene Expression Messy Genetic Algorithm (GEMGA) research. It presents extensive experimental results for large problems with massive multi-modality, non-uniform scaling, and overlapping sub-problems. All the experimental results corroborate the linear time performance of the GEMGA for a wide range of problems, that can be decomposed into smaller overlapping and non-overlapping sub-problems in the chosen representation. These results further support the scalable performance of the GEMGA. 1 Introduction The recent past has witnessed a growing interest in designing scalable evolutionary algorithms that inductively detect the decomposable partitions (sometimes called genetic linkage in the Genetic Algorithm (GA) literature[8]) of the optimization problem. Messy genetic algorithms [4, 6, 5, 7, 10, 3], Dependency trees [2], distribution estimation [15, 16], are some examples. For problems that can be decomposed into smaller subproblems in ..