Transfer batch scheduling using genetic algorithms

George Christopher Vosniakos (1) , Vasilis Millas (2)

1 Mechanical Engineering
2 Mech.Eng.

In this paper scheduling in a manufacturing system with transfer batches is examined. Transfer batches are considered as different batches although they stem from the same job. Genetic Algorithms determine the size of the transfer batches for each job and the final schedule with a makespan criterion. A novelty of the Genetic Algorithm developed is the twin chromosome encoding, the first chromosome representing the relative size (participation ratio) of each transfer batch with respect to the whole batch and the second chromosome applying in effect a dynamic heuristic dispatching rule representation for resolving operation antagonism. New crossover and mutation operators were employed for the first chromosome and standard operators for the second. The genetic algorithms were coded in C++ for better control. A 20 job × 8 machine shop is used as a test-case. Results favour Genetic Algorithms over heuristic procedures, but the latter close the gap with increase of the number of transfer batches. Design of Experiments was used to focus on the most promising Genetic Algorithm parameter value combinations.

Mots clés: Physical Sciences

George Christopher Vosniakos, Vasilis Millas. Transfer batch scheduling using genetic algorithms. International Journal of Production Research, 2007, 46 (04), pp.993-1016. ⟨10.1080/00207540600920843⟩. ⟨hal-00512942⟩