AN ALTERNATIVE HYBRID EVOLUTIONARY TECHNIQUE FOCUSED ON ALLOCATING MACHINES AND SEQUENCING OPERATIONS

FERNANDO DELBIANCO; FERNANDO TOHMÉ; MARIANO FRUTOS; FABIO MIGUEL

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS

GROWING SCIENCE

Lugar: Ottawa; Año: 2016 vol. 7 p. 585 - 596

We present here a hybrid algorithm for the Flexible Job-Shop Scheduling Problem (FJSSP). This problem involves the optimal use of resources in a flexible production environment in which each operation can be carried out by more than a single machine. Our algorithm allocates, in a first step, the machines to operations and in a second stage it sequences them by integrating a Multi-Objective Evolutionary Algorithm (MOEA) and a path-dependent search algorithm (Multi-Objective Simulated Annealing), which is enacted at the genetic phase of the procedure. The joint interaction of those two components yields a very efficient procedure for solving the FJSSP. An important step in the development of the algorithm was the selection of the right MOEA. Candidates were tested on problems of low, medium and high complexity. Further analyses showed the relevance of the search algorithm in the hybrid structure. Finally, comparisons with other algorithms in the literature indicate that the performance of our alternative is good.