An elaborative unit cost structure-based fuzzy economic production quantity model

被引:9
作者
Chang, Ping-Teng [1 ]
Chang, Ching-Hsiang [1 ]
机构
[1] Tunghai Univ, Dept Ind Engn & Enterprise Informat, Taichung 407, Taiwan
关键词
economic production quantity; inventory model; unit cost structure; fuzzy interval analysis; fuzzy arithmetic; fuzzy function optimization;
D O I
10.1016/j.mcm.2005.02.012
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The purpose of this paper is to investigate and propose a fuzzy extended economic production quantity model based on an elaboratively modeled unit cost structure. This unit cost structure consists of the various lot-size correlative components such as on-line setups, off-line setups, initial production defectives, direct material, labor, and depreciation in addition to lot-size noncorrelative items. Thus, the unit cost is correlatively modeled to the production quantity. Therefore, the modeling or the annual total cost function developed consists of not only annual inventory and setup costs but also production cost. Moreover, via the concept of fuzzy bluffed optimal argument and the vertex method of the alpha-cut fuzzy arithmetic (or fuzzy interval analysis), two solution approaches are proposed: (1) a fuzzy EPQ and (2) a compromised crisp EPQ in the fuzzy sense. An optimization procedure, which can simultaneously determine the alpha-cut-vertex combination of fuzzy parameters and the optimizing decision variable value, is also proposed. The sensitivity model for the fuzzy total cost and thus EPQ to the various cost factors is provided. Finally, a numerical example with the original data collected from a firm demonstrates the usefulness of the new model. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1337 / 1356
页数:20
相关论文
共 23 条
[1]   Multi-item EOQ inventory model with varying holding cost under two restrictions: A geometric programming approach [J].
AbouElAta, MO ;
Kotb, KAM .
PRODUCTION PLANNING & CONTROL, 1997, 8 (06) :608-611
[2]  
[Anonymous], 2001, Operations Management
[3]   RANKING OF FUZZY-SETS BASED ON THE CONCEPT OF EXISTENCE [J].
CHANG, PT ;
LEE, ES .
COMPUTERS & MATHEMATICS WITH APPLICATIONS, 1994, 27 (9-10) :1-21
[4]   Fuzzy strategic replacement analysis [J].
Chang, PT .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2005, 160 (02) :532-559
[5]   Fuzzy production inventory for fuzzy product quantity with triangular fuzzy number [J].
Chang, SC .
FUZZY SETS AND SYSTEMS, 1999, 107 (01) :37-57
[6]   VERTEX METHOD FOR COMPUTING FUNCTIONS OF FUZZY VARIABLES [J].
DONG, WM ;
SHAH, HC .
FUZZY SETS AND SYSTEMS, 1987, 24 (01) :65-78
[7]  
Dubois D, 2000, HDB FUZZ SET SER, V7, P483
[8]  
Dubois D., 1987, ANAL FUZZY INFORMATI, V1, P3
[9]  
Dubois D., 1980, FUZZY SET SYST
[10]   Fuzzy weighted average: A max-min paired elimination method [J].
Guh, YY ;
Hon, CC ;
Wang, KM ;
Lee, ES .
COMPUTERS & MATHEMATICS WITH APPLICATIONS, 1996, 32 (08) :115-123