Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

Algorithm 1

A simple GA.

Start

Encode initial solutions in chromosomes

Randomly generate an initial population of chromosomes

Compute fitness for each chromosome in the population

Repeat the following until number of offsprings <= number of chromosomes,

(i) Select a pair of parent chromosomes using selection method

(ii) Crossover the selected pair with the crossover probability at randomly chosen point to form two offsprings

(iii) Mutate the offsprings with mutation probability at all locations

Obtain new set of chromosomes

Replace the current population with new population using replacement strategy

Compute fitness

Generate new population until the fitness criteria is met

End