Abstract

This paper aims to address distributed flexible job shop scheduling problem (DFJSP) with sequence dependent setup times by minimizing the total energy consumption. This research proposed and formulated a mixed integer linear programming (MILP) model with an early optimization termination criterion to solve the DFJSP. Furthermore, this model is extended to consider electricity consumption by introducing the objective function of energy usage in the form of processing energy, setup energy, and idle energy consumption, with strategy to shutdown machines when the machines are in idle state. A constraint programming model and a meta-heuristic algorithm in the form of a combination of Genetic and NEH algorithm (NEH-GA) is proposed and compared with the MILP model. The results show that the MILP model achieves optimality within reasonable time and performs better than constraint programming model when problem complexity is small, whereas constraint programming tends to do better when the problem complexity is large. The proposed meta-heuristic algorithm performs the best in terms of computation time when the problem complexity is large albeit not guaranteeing an optimal solution.