Abstract
This article considers the flow shop problem of minimising the total weighted completion time in which the processing times of jobs are variable according to general position weighted learning effects. Two simple heuristics are proposed, and their worst-case error bounds are analysed. In addition, some complex heuristics (including simulated annealing algorithms) and a branch-and-bound algorithm are proposed as solutions to this problem. Finally, computational experiments are performed to examine the effectiveness and efficiency of the proposed algorithms.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Table A9. Tests of between-subjects effects to SA1 for large-sized instances.
Table A10. Tests of between-subjects effects to SA2 for large-sized instances.