KARTHIKEYAN, S. ... et al, 2015. A hybrid discrete firefly algorithm for solving multi-objective flexible job shop scheduling problems. International Journal of Bio-Inspired Computation, 7 (6), pp. 386-407.
Firefly Algorithm (FA) is a nature-inspired optimization algorithm that can be successfully
applied to continuous optimization problems. However, lot of practical problems are
formulated as discrete optimization problems. In this paper a hybrid discrete firefly
algorithm (HDFA) is proposed to solve the multi-objective flexible job shop scheduling
problem (FJSP). FJSP is an extension of the classical job shop scheduling problem that
allows an operation to be processed by any machine from a given set along different
routes. Three minimization objectives - the maximum completion time, the workload of
the critical machine and the total workload of all machines are considered simultaneously.
This paper also proposes firefly algorithm’s discretization which consists of constructing a
suitable conversion of the continuous functions as attractiveness, distance and movement,
into new discrete functions. In the proposed algorithm discrete firefly algorithm (DFA) is
combined with local search (LS) method to enhance the searching accuracy and
information sharing among fireflies. The experimental results on the well-known
benchmark instances and comparison with other recently published algorithms shows that the proposed algorithm is feasible and an effective approach for the multi-objective
flexible job shop scheduling problems.
This paper was accepted for publication in the journal International Journal of Bio-Inspired Computation and the definitive published version is available at http://dx.doi.org/10.1504/IJBIC.2015.073165