Modified JAYA algorithm for solving the flexible job shop scheduling problem considering worker flexibility and energy consumption

摘要

This paper investigates a flexible job shop scheduling problem with worker flexibility and energy consumption. A modified JAYA algorithm (MJAYA) is developed to minimise the total energy consumption. In the MJAYA, three improvement strategies are used to improve the algorithm's performance, such as Modified Individual Updating (MIU) method, Adaptive Mutation Operator (AMO) and Local Search Strategy (LSS). The MIU is developed to improve the exploration ability by adding a random term to the original updating equation. The AMO is used to keep the population diversity. In addition, The LSS is employed to enhance the local search capacity. Finally, extensive simulations are performed to validate the effectiveness of the proposed MJAYA algorithm. Experimental data show that the MJAYA algorithm is effective for solving the considered problem.