A Cooperative Solver for Single Machine Total Weighted Tardiness Scheduling Problem

In this paper, we aim to present a novel efficient approach called improved genetic simulated annealing algorithm (IGASA) in order to minimize the total weighted tardiness of n jobs on a single machine, which is recognized in the literature as a strong NP-hard Problem. The proposed model takes advantages of the genetic algorithm (GA) as a global search strategy and the capability of the improved simulated annealing (ISA) technique to improve solution quality in local regions. Experimental results on a set of benchmarks demonstrated the potent of our developed algorithm to find a good solutions which are significantly outperforms some other published works.