A multiple-criteria real-time scheduling approach for multiple-load carriers subject to LIFO loading constraints

• Published in: International journal of production research Vol. 49; no. 16; pp. 4787 - 4806
• Main Authors: Chen, Ci, Xi, Li-feng, Zhou, Bing-hai, Zhou, Shen-shen
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis Group 15.08.2011; Taylor & Francis; Taylor & Francis LLC
• Subjects: Applied sciences; Assembly lines; Automotive engineering; Carriers; Criteria; Decision theory. Utility theory; Exact sciences and technology; Materials handling; multi-criteria decision making; neural network applications; Operational research and scientific management; Operational research. Management science; Operations research; Product mixes; Production scheduling; Real time; Scheduling; Scheduling, sequencing; Simulation; Studies; Assembly line; Motor car; neural network applications; LIFO system; Multicriteria analysis; Decision making; Materials handling; Profit; Scheduling; Neural network; Real time; multi-criteria decision making
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207543.2010.510486

This paper studies the problem of scheduling a multiple-load carrier subject to last-in-first-out loading constraints in an automobile assembly line. Two scheduling criteria, the throughput of the assembly line and the material handling distance, are considered in order to maximise the profit of the assembly line. Different from other studies, the product mix and weights of the scheduling criteria are considered to be variable. A scheduling approach is proposed for the problem. At moments when the product mix or weights of the scheduling criteria change, the scheduling approach can select an appropriate rule from a set of given rules. In this study, the proposed approach is compared with other approaches by simulation in order to verify the performance of the proposed approach. The results indicate that, when the product mix and weights of the scheduling criteria are variable, the proposed scheduling approach outperforms other approaches.