A Discrete Particle Swarm Optimization Algorithm for Single Machine Total Earliness and Tardiness Problem with a Common Due Date

In this paper, a discrete particle swarm optimization (DPSO) algorithm is presented to solve the single machine total earliness and tardiness penalties with a common due date. A modified version of HRM heuristic presented by Hino et al. in [7], here we call it M_HRM, is also presented to solve the problem. In addition, the DPSO algorithm is hybridized with the neighborhood search algorithm to further improve the solution quality. The performance of the proposed DPSO algorithm is tested on 280 benchmark instances up to 1000 jobs from the OR Library. The computational experiments showed that the proposed DPSO algorithm has generated better results, in terms of both percent deviations from the upper bounds in Biskup and Feldmann [1] and computational time, than the existing approaches in the literature.