  This paper presents a memory-optimized metadata-based data structure for
implementation of binary chromosome in Genetic Algorithm. In GA different types
of genotypes are used depending on the problem domain. Among these, binary
genotype is the most popular one for non-enumerated encoding owing to its
representational and computational simplicity. This paper proposes a
memory-optimized implementation approach of binary genotype. The approach
improves the memory utilization as well as capacity of retaining alleles.
Mathematical proof has been provided to establish the same.
