A heuristic approach to a single stage assembly problem with transportation allocation

被引:8
|
作者
You, Peng-Sheng [1 ]
Hsieh, Yi-Chih [2 ]
机构
[1] Natl ChiaYi Univ, Grad Inst Mkt & Logist Transportat, Chiayi 600, Taiwan
[2] Natl Formosa Univ, Dept Ind Management, Huwei 632, Yunlin, Taiwan
关键词
Assembly scheduling; Transportation allocation; Heuristic; Assembly delays; ELECTRONICS SUPPLY CHAIN; VEHICLE-ROUTING PROBLEM; AIR-TRANSPORTATION; TIME WINDOWS; INTEGRATED INVENTORY; SCHEDULING PROBLEM; GENETIC-ALGORITHM; DELIVERY; OPTIMIZATION; POLICIES;
D O I
10.1016/j.amc.2012.04.066
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Determining assembly scheduling and transportation allocation are two practical problems that industries face, such as the electronics and health products industries. Problems associated with assembly scheduling mainly focus on how to determine the orders' processing sequence on the assembly line in order to minimize the waiting times before they are flown to their destinations. Problems associated with transportation allocation arise in the system of assigning processed orders to transport modes with the purpose of minimizing penalties from earliness and tardiness. To minimize overall delivery costs, businesses should decide on assembly scheduling and transportation allocation decision simultaneously. However, since simultaneously making these two decisions is not an easy task, most of the works done on them usually deal with these two problems separately. Apart from previous works, this paper establishes a mixed integer programming model that deals with these problems simultaneously. Due to the computational complexity of the problem, this paper develops a hybrid heuristic algorithm to solve this problem, and we evaluate the performance of the presented heuristic algorithm with the well-known GAMS/BARON and Lingo commercial software, which tests the heuristic algorithm on randomly-generated problems. The presented heuristic algorithm is shown to perform well compared with well-known commercial software. (c) 2012 Elsevier Inc. All rights reserved.
引用
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页码:11100 / 11111
页数:12
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