Earliness/tardiness flow-shop scheduling under uncertainty

For unconventional scheduling problems, both job sequence and starting time of every operation must be optimized, which increases the difficulties of solving this kind of problem. In this paper, we advanced a jointed algorithm for solving flow-shop earliness/tardiness problem based on genetic algorithm and heuristic algorithm. Hierarchy scheduling paradigm was introduced. First, the genetic algorithm is used to determine preferably scheduling sequence. Second, a kind of new heuristic algorithm was put forward to adjust the starting times for the present schedule. Where, the heuristic algorithm determined what time and how long every idle time should be. The object of this paper is to minimize the total earliness and tardiness penalties of all the jobs. The numerical results obtained prove the correctness and efficiencies of the jointed algorithm