Showing 3 results for Batching
Rashed Sahraeian,
Volume 25, Issue 1 (2-2014)
Abstract
In this paper the problem of serial batch scheduling in a two-stage hybrid flow shop environment with minimizing Makesapn is studied. In serial batching it is assumed that jobs in a batch are processed serially, and their completion time is defined to be equal to the finishing time of the last job in the batch. The analysis and implementation of the prohibited transference of jobs among the machines of stage one in serial batch is the main contribution of this study. Machine set-up and ready time for all jobs are assumed to be zero and no Preemption is allowed. Machines may not breakdown but at times they may be idle. As the problem is NP-hard, a genetic algorithm is developed to give near optimal solutions. Since this problem has not been studied previously, therefore, a lower bound is developed for evaluating the performance of the proposed GA. Many test problems have been solved using GA and results compared with lower bound. Results showed GA can obtain a near optimal solution for small, median and large size problems in reasonable time.
Morteza Rasti-Barzoki, Ali Kourank Beheshti, Seyed Reza Hejazi,
Volume 27, Issue 2 (6-2016)
Abstract
This paper addresses a production and outbound distribution scheduling problem in which a set of jobs have to be process on a single machine for delivery to customers or to other machines for further processing. We assume that there is a sufficient number of vehicles and the delivery costs is independent of batch size but it is dependent on each trip. In this paper, we present an Artificial Immune System (AIS) for this problem. The objective is to minimize the sum of the total weighted number of tardy jobs and the batch delivery costs. A batch setup time has to be added before processing the first job in each batch. Using computational test, we compare our method with an existing method for the mentioned problem in literature namely Simulated Annealing (SA). Computational tests show the significant improvement of AIS over the SA.
Javad Rezaeian, Masoud Shafipour,
Volume 28, Issue 3 (9-2017)
Abstract
This research deals with a hybrid flow shop scheduling problem with parallel batching, machine eligibility, unrelated parallel machine, and different release dates to minimize the sum of the total weighted earliness and tardiness (ET) penalties. In parallel batching situation, it is supposed that number of machine in some stages are able to perform a certain number of jobs simultaneously. Firstly, with respect to the proposed problem a mixed integer linear programming model is developed. Since the problem is NP-hard, for solving large size problems, a hybrid meta-heuristic algorithm which combines artificial immune system and simulated annealing is proposed. The performance of hybrid algorithm is tested by some numerical experiments and the results show its superiority to the other two algorithms.
