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

被引:16
作者
Chen, Ci [2 ]
Xi, Li-feng [2 ]
Zhou, Bing-hai [1 ]
Zhou, Shen-shen [2 ]
机构
[1] Tongji Univ, Sch Mech Engn, Shanghai 201804, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai 200240, Peoples R China
基金
美国国家科学基金会;
关键词
materials handling; neural network applications; multi-criteria decision making; scheduling; FLEXIBLE MANUFACTURING SYSTEMS; AUTOMATED GUIDED VEHICLES; NEURAL-NETWORKS; DISPATCHING RULES; ENVIRONMENT; SELECTION; SIMULATION;
D O I
10.1080/00207543.2010.510486
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:4787 / 4806
页数:20
相关论文
共 24 条
[1]   A review on evolution of production scheduling with neural networks [J].
Akyol, Derya Eren ;
Bayhan, G. Mirac .
COMPUTERS & INDUSTRIAL ENGINEERING, 2007, 53 (01) :95-122
[2]   A multi-criteria adaptive control scheme based on neural networks and fuzzy inference for DRC manufacturing systems [J].
Araz, Oezlem Uzun ;
Salum, Latif .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2010, 48 (01) :251-270
[3]   Neural network-based adaptive production control system for a flexible manufacturing cell under a random environment [J].
Arzi, Y ;
Iaroslavitz, L .
IIE TRANSACTIONS, 1999, 31 (03) :217-230
[4]   A STATE-OF-THE-ART SURVEY OF DISPATCHING RULES FOR MANUFACTURING JOB SHOP OPERATIONS [J].
BLACKSTONE, JH ;
PHILLIPS, DT ;
HOGG, GL .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1982, 20 (01) :27-45
[5]   An action strategy generation framework for an on-line scheduling and control system in batch processes with neural networks [J].
Chen, W ;
Muraki, M .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1997, 35 (12) :3483-3507
[6]   THE USE OF NEURAL NETWORKS IN DETERMINING OPERATIONAL POLICIES FOR MANUFACTURING SYSTEMS [J].
CHRYSSOLOURIS, G ;
LEE, M ;
DOMROESE, M .
JOURNAL OF MANUFACTURING SYSTEMS, 1991, 10 (02) :166-175
[7]   SIMULATION STUDIES IN JOB SHOP SCHEDULING .1. A SURVEY [J].
KIRAN, AS ;
SMITH, ML .
COMPUTERS & INDUSTRIAL ENGINEERING, 1984, 8 (02) :87-93
[8]   Effect of manufacturing system constructs on pick-up and drop-off strategies of multiple-load AGVs [J].
Lee, J ;
Srisawat, T .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2006, 44 (04) :653-673
[9]   Load selection of automated guided vehicles in flexible manufacturing systems [J].
Lee, J ;
Tangjarukij, M ;
Zhu, Z .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1996, 34 (12) :3383-3400
[10]   Optimal routing of multiple-load AGV subject to LIFO loading constraints [J].
Levitin, G ;
Abezgaouz, R .
COMPUTERS & OPERATIONS RESEARCH, 2003, 30 (03) :397-410