Worst case performance scheduling facing uncertain disruption in a continuous casting process

Conference proceedings article

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

ไม่พบข้อมูลที่เกี่ยวข้อง

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Worapradya K., Thanakijkasem P.

ผู้เผยแพร่: Hindawi

ปีที่เผยแพร่ (ค.ศ.): 2010

หน้าแรก: 291

หน้าสุดท้าย: 295

จำนวนหน้า: 5

ISBN: 9781424485031

นอก: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-78751680954&doi=10.1109%2fIEEM.2010.5674467&partnerID=40&md5=14da94e16f7738f91f5ac90c9ac5e253

ภาษา: English-Great Britain (EN-GB)

ดูบนเว็บไซต์ของสำนักพิมพ์

บทคัดย่อ

Several disruptions (e.g., machine failure, quality problem, etc.) in a steel production often occur in practice and lead to a delay in the production. Many schedule changes in a short period of time lead to an unstable production. Therefore, a robust predictive scheduling, which takes the disruption effect into account, is a more suitable choice for handling the daily small disruption. In this paper, a worst case performance scheduling via Minimax optimization for a multi-continuous casting is presented. By this approach, each uncertain disruption event is defined to be a possible scenario. A set of factory maintenance information (e.g., a machine reliability/availability) is utilized for constructing and illustrating the uncertain disruption model. Two loops of Genetic Algorithm (GA); one searching the worst scenario for each feasible schedule and another searching an optimal schedule, are performed. The objective function is formulated in terms of the steel production costs. The robust performance based on the factory data is demonstrated via Monte Carlo simulation. It shows that the worst case performance schedule can robustly handle the uncertain daily disruption. ฉ2010 IEEE.

คำสำคัญ

Minimax optimization