Volume 33, Issue 2 (IJIEPR 2022)                   IJIEPR 2022, 33(2): 1-17 | Back to browse issues page

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ÇETİNKAYA F C, BORAN YOZGAT G. Customer Order Scheduling with Job-Based Processing and Lot Streaming In A Two-Machine Flow Shop. IJIEPR 2022; 33 (2) :1-17
URL: http://ijiepr.iust.ac.ir/article-1-1308-en.html
Customer Order Scheduling with Job-Based Processing and Lot Streaming In A Two-Machine Flow Shop
FERDA CAN ÇETİNKAYA 1, GÜNCE BORAN YOZGAT2
1- Department of Industrial Engineering, Çankaya University , cetinkaya@cankaya.edu.tr
2- Defense Industries Research and Development Institute, The Scientific and Technological Research Council of Turkey
Abstract:   (2755 Views)
This paper considers a customer order scheduling (COS) problem in which each customer requests a variety of products processed in a two-machine flow shop. A sequence-independent attached setup for each machine is needed before processing each product lot. We assume that customer orders are satisfied by the job-based processing approach in which the same products from different customer orders form a product lot (job). Each customer order for a product is processed as a sublot (a batch of identical items) of the product lot by applying the lot streaming (LS) idea in scheduling. We assume that all sublots of the same product must be processed together by the same machine without intermingling the sublots of other products. The completion time of a customer order is the completion time of the product processed as the last product in that order. All products in a customer order are delivered in a single shipment to the customer when the processing of all the products in that customer order is completed. We aim to find an optimal schedule with a product lots sequence and the sequence of the sublots in each job to minimize the sum of completion times of the customer orders. We have developed a mixed-integer linear programming (MILP) model and a multi-phase heuristic algorithm for solving the problem. The results of our computational experiments show that our model can solve the small-sized problem instances optimally. However, our heuristic algorithm finds optimal or near-optimal solutions for the medium- and large-sized problem instances in a short time.
Keywords: Customer order scheduling, Job-based processing, Lot streaming, Two-machine flow shop, Total completion time, Mixed-integer linear programming, Heuristic algorithm
Full-Text [PDF 1072 kb]   (1190 Downloads)    
Type of Study: Research | Subject: Operations Managment
Received: 2021/08/11 | Accepted: 2022/02/26 | Published: 2022/06/30
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