A simulation optimization approach for flow-shop scheduling problem: a canned fruit industry

被引：7
作者：
Azadeh, A. [1 ,2 ]
Maleki-Shoja, B. [1 ,2 ]
Sheikhalishahi, M. [1 ,2 ]
Esmaili, A. [1 ,2 ]
Ziaeifar, A. [1 ,2 ]
Moradi, B. [1 ,2 ]
机构：
[1] Univ Tehran, Univ Coll Engn, Sch Ind Engn, Tehran, Iran
[2] Univ Tehran, Univ Coll Engn, Ctr Excellence Intelligent Based Expt Mech, Tehran, Iran
来源：
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 2015年 / 77卷 / 1-4期
基金：
美国国家科学基金会;
关键词：
Canned fruit industry; Flow-shop scheduling; Artificial neural network; Simulation optimization; Cost; SINGLE-MACHINE; NEURAL-NETWORK; DISPATCHING RULE; HYBRID APPROACH; TARDINESS; ALGORITHM; MAKESPAN; MODEL;
D O I：
10.1007/s00170-014-6488-x
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Flow-shop scheduling is one of the major problems in many manufacturing systems. Canned fruit is one of the industries in which the flow-shop scheduling has already been used. In this paper, an aggregated artificial neural network and simulation modeling approach are proposed to find optimal solution for such cases. Therefore, artificial neural network and simulation (ANNS) approach is introduced and used as a new approach to solve a certain flow-shop scheduling problem with the objective of minimizing total cost. In this research, flow-shop scheduling problem with parallel identical machines is investigated. The proposed approach is compared with the previous works, and the performance of the proposed approached is studied on a test problem. Experimental results show the superiority of the presented approach over conventional simulation approaches.
引用
收藏
页码：751 / 761
页数：11
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