The multi-objective scheduling research derives its importance from the need to address the real scheduling problem, which is transformed in a single objective. A schedule that is good for one objective function may in fact be quite insignificant for another. Decision-makers must carefully evaluate the trade-offs involved in considering several different criteria in practical scheduling applications. In this paper, a hybrid approach that combines ant system optimisation and fuzzy logic concept is introduced to facilitate the multiobjective optimisation Flexible Job Shop Scheduling Problem (FJSP). The scheduling problem has two main characteristics namely the flexibility of machines that have the possibility to process all the operations with different processing times and the taking into account different and independent criteria that must be optimized simultaneously. The considered objectives are to minimise makespan, the workload of the critical machine and the total workload of machines. Based on the concept of the ant system and fuzzy controller, the ant system parameters are controlled for multi-objective evolution. The efficiency of the proposed approaches is compared with other approaches by defining the lower bounds for each criterion.
Flexible production, job-shop scheduling, Ant colony, Fuzzy controller, Tabu search, makespan, multi-objective optimisation, lower bounds.
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