A new bi-level meta-heuristic approach for a single machine JIT-scheduling in the batch delivery system with controllable due dates

This paper considers pre-emption in single machine scheduling problem with batch delivery and release times in which due dates are controllable as realistic assumptions in the manufacturing environment. The objective is to minimise the lateness, holding, delivery and due date assignment costs. In this study set up time is independent and it follows of a function based on the number of loading on machine in each batch. We proposed a new solution methodology, as this problem is proven to be NP-hard, hence two meta-heuristics namely: bi-level double genetic algorithm (BDGA) and bi-level hybrid genetic and simulated annealing algorithms (BSGA) are employed for solving the problem. Taguchi method is applied to tune the parameters of proposed algorithms. The performance of the proposed algorithms are measured in terms of relative percent deviation (RPD) and computational time, the computational results reveal that statistically BDGA is better than BSGA based on RPD and computational time.