Vectorization of local search for solving flow-shop scheduling problem on Xeon Phi™ MIC co-processors

Abstract : This paper aims to propose a vectorizable cost function for the permutation flow-shop problem (PFSP) with the makespan criterion. This vectorization has been tested on a Xeon Phi core, using a local search. Indeed, Xeon Phi co-processors require vectorization in order to get the best performance from the device. Taillard's benchmark instances are used for the validation of the algorithm. The obtained results show that vectorization is more efficient as the number of jobs and the number of machines increase. Speedups up to 4.5× are recorded.