Fuzzy multi-product constraint newsboy problem

In this paper, we consider the multi-product newsboy problem with fuzzy demands under budget constraint. Since the demands of products are often fuzzy in real life, the profit of the newsboy is fuzzy too. We develop three types of models under different criteria: EVM model, DCP model and CCP model....

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Veröffentlicht in:Applied mathematics and computation Jg. 180; H. 1; S. 7 - 15
Hauptverfasser: Shao, Zhen, Ji, Xiaoyu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY Elsevier Inc 01.09.2006
Elsevier
Schlagworte:
Applied sciences
Exact sciences and technology
Fuzzy programming
Genetic algorithm
Mathematical programming
Mathematics
Newsboy problem
Numerical analysis
Numerical analysis. Scientific computation
Numerical methods in mathematical programming
Numerical methods in mathematical programming, optimization and calculus of variations
Operational research and scientific management
Operational research. Management science
Sciences and techniques of general use
Single-period inventory
Fuzzy programming
Single-period inventory
Genetic algorithm
Newsboy problem
Numerical analysis
Applied mathematics
Profit
Objective function
Simulation model
ISSN:0096-3003, 1873-5649
Online-Zugang:Volltext
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Zusammenfassung:In this paper, we consider the multi-product newsboy problem with fuzzy demands under budget constraint. Since the demands of products are often fuzzy in real life, the profit of the newsboy is fuzzy too. We develop three types of models under different criteria: EVM model, DCP model and CCP model. In these models, the objective functions are to maximize the expected profit of newsboy, the chance of achieving a target profit and the profit which satisfies some chance constraints with at least some given confidence level, respectively. Furthermore, the hybrid intelligent algorithm based on genetic algorithm and fuzzy simulation is designed for these models. And some illustrating examples are given in order to show the application of these proposed models and algorithm.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2005.11.123