The flexible job shop scheduling problem is investigated

where the transportation resource and operation related setup time constraints are considered simultaneously. The objective is to minimize the maximum completion time and the energy consumption. To solve the problem

we propose an improved artificial bee colony algorithm

where each solution is represented by a two-dimensional vector

the scheduling vector is to record the operation processing sequence

and the machine assignment vector is to assign the candidate machine for each operation. In the decoding mechanism

the transportation and setup time constraints are investigated. For the local search approaches

we develop five types of neighborhood structures for the scheduling part

and a well-designed machine assignment neighborhood structure for the machine assignment vector. To enhance the global searching abilities

the simulated annealing acceptance method is embedded. Finally

the experiment comparisons verify the performance of the proposed algorithm.