Group Scheduling Problems Research Articles

Jointly solving the group scheduling and machining speed selection problems: A hybrid tabu search and simulated annealing approach

In a cellular manufacturing environment, once the machines and parts have been grouped the remaining tasks are sequencing part families and scheduling operations for the parts within each part family so that some planning goals such as minimization of tardiness can be achieved. This type of problem is called group scheduling and will be analysed in this paper. The solution of the group scheduling is affected by the machining speed specified for each operation since the completion time of each operation is a function of machining speed. As such, the group scheduling and machining speed selection problems should be simultaneously solved to provide meaningful solutions. This, however, further complicates the solution procedure. In view of this, a hybrid tabu-simulated annealing approach is proposed to solve the group scheduling problem. The main advantage of this approach is that a short term memory provided by the tabu list can be used to avoid solution re-visits while preserving the stochastic nature of the simulated annealing method. The performance of this new method has been tested and favourably compared with two other algorithms using tabu search and simulated annealing alone.

Combined heuristics for bi-level group scheduling problems

In this paper the comparative performance of several combined heuristics for solving bi-level group scheduling problems is investigated. At the first level, the sequence of parts within a part family/group is determined. While at the second, an appropriate sequence for groups of jobs is determined. Both single-pass and multiple-pass heuristics are selected for completely solving a group scheduling problem at both levels in order to minimize the makespan. Two different research questions are addressed. The first determines which of the combinations, each consisting of a single (Petrov, 1966 (PT)) and a multiple-pass heuristic (Logendran and Nudtasomboon, 1991 (LN); Campbell, Dudek and Smith, 1970 (CDS)), is a better performer. The second determines which of the two multiple-pass heuristics (LN or CDS) is a better performer, if used at both levels. The experiments have been setup as factorial designs with split-plots across the heuristics. Several test problems are solved for addressing the key issues raised in both questions. Results obtained show that, for research question 1, a combination given by LN at the first level, followed by PT at the second level is the most preferred arrangement. For research question 2, a combination represented by LN-LN outperforms CDS-CDS.

Group scheduling problem: Key to flexible manufacturing systems

We present an efficient heuristic algorithm for determining the sequence which minimizes the makespan of a group scheduling problem at the first level. The problem, therefore, focuses on scheduling of parts (jobs) in a part family. In the generation of partial schedules at each iteration, a job with a high mean total processing time is given a higher priority than others. An example problem, chosen from a real world application, is used to implement, the algorithmic steps. For this example, it has also been shown that the makespan determine by the proposed heuristic is smaller than that determined previously by two documented algorithms.

Combining petrov's heuristic and the CDS heuristic in group scheduling problems

Combining petrov's heuristic and the CDS heuristic in group scheduling problems