Lunar cycle inspired PSO for single machine total weighted tardiness scheduling problem

In the large scale Single machine total weighted tardiness scheduling problem (SMTWTSP) is a group of not-interrelated tasks having different parameters to be executed on one machine. The problem’s objective is to identify the minimum total weighted tardiness using a newly developed variant of the particle swarm optimization (PSO) algorithm. In the past, the PSO algorithm has proved itself as an efficient swarm intelligence based strategy to solve complex combinatorial problems. Here, in this article, the lunar cycle inspired local search technique is assimilated into PSO, and the designed PSO variant is termed as lunar cycle inspired PSO (LCPSO). The performance of the designed LCPSO is tested over 25 large SMTWTSP instances of job size 1000. The reported results show that the designed LCPSO is a competitive PSO variant that can be applied to provide an effective solution for the SMTWTSP type combinatorial optimization problem.