Due to these features, in this paper ISFHA is utilized to obtain the best OFV for SRFL problem.
Compute the OFV of the mutated sub-chromosome, compare with the OFV of the parent chromosome and choose the chromosome, according to the best OFV.
Assume and compute C is the OFV for each population P
Compare OFV of crossover sub-chromosome with the parent chromosome
Compare OFV and Choose the best OFV based chromosome
The key Goal of this paper is, to obtain a minimum cost is OFV. Chromosome denotes a number of machines placed in an order to create a single row layout as
After the crossover, the OFV is calculated for the chromosome and check the cross over OFV is lesser than the parent chromosome OFV, then the parent chromosome is replaced by the crossover chromosome, else, the parent chromosome is retained.
After the inverse mutation, the OFV is calculated for the mutated chromosome and check the mutated chromosome OFV is lesser than the parent chromosome OFV, then the parent chromosome is replaced by the mutated chromosome, else, the parent chromosome is retained.
After the single point mutation, the OFV is calculated for the mutated chromosome and check the mutated chromosome OFV is lesser than the parent chromosome OFV, then the parent chromosome is replaced by the mutated chromosome, else, the parent chromosome is retained.
Now, eliminate the chromosomes which are having OFV lesser than Average(1/OFV).
The robust replace heuristic method is applied to eliminate the highest OFV based chromosomes and replace them by newly generated chromosomes.
After the inverse and single point mutation, the OFV is calculated for the mutated chromosome and check the mutated chromosome OFV is lesser than the parent chromosome OFV, if, then the parent chromosome is replaced by the mutated chromosome, else, the parent chromosome is retained.