Abstract | ||
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Proposed model has been developed incorporating three level trade credit policy.Selling price, customers credit period and customers credit amount induced demand.Model is formulated in crisp, fuzzy and rough environments.Solutions of imprecise models are found without using crisp equivalent of objectives.The marketing decision has made from both wholesalers and retailers point of view. In this paper, an integrated supply chain model has been developed under three level trade credit policy with price, credit period and credit amount dependent demand, where a supplier offers a credit period to his/her wholesaler to boost the demand of the item. Due to this facility, wholesaler also offers a credit period to his/her retailer and the same practice is followed by the retailer to increase the base demand of the item. Here it is assumed that, both wholesaler and retailer enjoy the same full credit facility but retailer just offers the partial trade credit to his/her customers. The main purpose of this paper is to maximize the joint profit of the wholesaler and the retailer. Model is formulated in crisp, fuzzy and rough environments. Here, a Particle Swarm Optimization (PSO) algorithm is used to find marketing decision for the proposed models. For fuzzy model, credibility measure of fuzzy event and for rough model, trust measure of rough event are used to compare the corresponding objectives for PSO. Models are illustrated with numerical examples and some parametric studies are performed. |
Year | DOI | Venue |
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2017 | 10.1016/j.cie.2017.02.007 | Computers & Industrial Engineering |
Keywords | Field | DocType |
Supply chain,Price, credit period and credit amount dependent demand,Three level trade credit,PSO | Particle swarm optimization,Fuzzy model,Credibility,Microeconomics,Fuzzy logic,Credit valuation adjustment,Parametric statistics,Supply chain,Trade credit,Engineering | Journal |
Volume | Issue | ISSN |
106 | C | 0360-8352 |
Citations | PageRank | References |
6 | 0.45 | 9 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
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Prasenjit Pramanik | 1 | 13 | 1.96 |
Manas Kumar Maiti | 2 | 236 | 20.68 |
Manoranjan Maiti | 3 | 514 | 47.77 |