DocumentCode :
2636325
Title :
A Product Mix Problem Based on Maximization of the Total Profit and Reduction of Excessive Inventories Including Uncertainty
Author :
Hasuike, Takashi ; Ishii, Hiroaki
Author_Institution :
Grad. Sch. of Inf. Sci. & Technol., Osaka Univ., Osaka
fYear :
2008
fDate :
18-20 June 2008
Firstpage :
282
Lastpage :
282
Abstract :
This paper considers a product mix problem both maximizing the total future profit and reducing excessive inventories including uncertainty with respect to future profits and customers´ demands. Furthermore, since a decision maker has a goal with respect to the total future profit and each inventory of the product, in this paper, aspiration levels for them are also introduced. The proposal product mix problem is formulated as a multi-criteria programming problem considering maximizing all aspiration levels assumed to be fuzzy goals. Then, since each future return and customer´s demand are assumed to be random variables, this problem including randomness is basically formulated as a multi-criteria stochastic programming problem. Since it is hard to solve it analytically, the transformations into deterministic equivalent problems are introduced and the efficient solution methods are constructed.
Keywords :
fuzzy set theory; inventory management; production planning; profitability; stochastic programming; aspiration level maximization; customer demand; decision making; deterministic equivalent problem; excessive inventory reduction; future profit; future return; fuzzy goal; multicriteria stochastic programming problem; product inventory; product mix problem; random variables; total profit maximization; Costs; Electric breakdown; Information analysis; Information science; Mathematical programming; Production planning; Proposals; Random variables; Stochastic processes; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-0-7695-3161-8
Electronic_ISBN :
978-0-7695-3161-8
Type :
conf
DOI :
10.1109/ICICIC.2008.80
Filename :
4603471
Link To Document :
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