Genetic Algorithm for flowshop scheduling problem using data oriented operators
Abstract
The general flowshop scheduling problem is approximately solved using a genetic algorithm. Chromosomes are classically encoded using permutation strings for each machine. The data-oriented operators use both the permutation strings and problem instances. The beginning of one parent is copied inside the first offspring which is completed with a priority rule generator using data of the second parents. The second offspring is obtained in a similar way. Several cross-over operators are designed. Some of them work only on the permutation encoding, other ones are data oriented.