A simulated annealing heuristic for scheduling to minimize mean weighted tardiness in a flowshop with sequence-dependent setup times of jobs–a case study
The problem of scheduling in a flowshop is considered, with the objective of minimizing the mean weighted tardiness. A case study is carried out in a drill-bit manufacturing industry. The problem encountered in the present study is different from the conventional flowshop scheduling problem in that the setup times are separated from process times and are sequence-dependent. A heuristic algorithm, based on simulated annealing (SA), is developed for scheduling in this flowshop. A method is presented for obtaining the initial seed sequence for the SA algorithm. A new exponential acceptance function and a new scheme for generating the neighbourhood, called the random insertion perturbation scheme (RIPS), are proposed. The stopping criteria make use of the temperature value and the value of freeze counter that is determined by the number of accepted and generated sequences. The SA heuristic is evaluated against existing heuristics and the results of computational evaluation reveal that the proposed heuristic performs much better. © 1997 Taylor & Francis Ltd.
An experimental evaluation of heuristics for scheduling in a real-life flowshop with sequence-dependent setup times of jobs
This paper deals with the development and evaluation of heuristics for scheduling in a real-life flowshop. The case study differs from the conventional flowshop scheduling problem in that the setup times of jobs are separated from process times and are sequence-dependent. We present a heuristic algorithm that makes use of simulated annealing (SA) technique. We also present a perturbation scheme in the SA algorithm. The proposed and existing heuristics are evaluated for scheduling to minimize the maximum weighted tardiness of a job and total weighted tardiness of jobs. The results of the computational evaluation reveal that the proposed heuristic performs much better than the existing ones.