Harris Hawks Optimization for Solving Flexible Jobshop Scheduling Problem Considering Energy Consumption

Abstract

Industrial scheduling problem has always been one of the key problems in manufacturing and management planning enterprises. The previous studies mainly concentrate on the optimization of maximum completion time. With the increasing shortage of non-renewable resources and the increasing demand for industrial energy, the energy crisis increasingly restricts production and living needs. Consider the above issues, this paper designs a FJSP with consideration of energy consumption (EFJSP). Meanwhile, an advanced swarm intelligence optimization algorithm: Harris Hawks Optimization (HHO), is introduced to solve the EFJSP. In the experiment, we formulated 4 FJSP instances to examine the performance of the HHO. The results obtained by the HHO compared with the other five classic metaheuristic algorithms. The comparison result displays that our algorithm far exceeds other algorithms in solving EFJSP.