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Inventory Policy with Stock, Price and Credit-Linked Demand: A Fuzzy Genetic Algorithm Approach

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  • Partha Guchhait

    (Vidyasagar University, India)

  • Pravash Kumar Giri

    (Vidyasagar University, India)

  • Manas Kumar Maiti

    (Mahishadal Raj College, India)

  • Manoranjan Maiti

    (Vidyasagar University, India)

Abstract

An inventory control problem under two-level trade-credit policy with fuzzy inventory costs is proposed where supplier provides not only a credit-period for settling account but also a cash discount to the retailers. Due to this advantage the retailer also offers a fixed credit period to all its customers to boost the demand. Demand also depends on stock and selling price. A Genetic Algorithm (GA) with chromosome’s life-time dependent varying population size is used to solve the model where, at the time of generation of initial population, diversity in the population is maintained using information entropy theory. In the algorithm crossover probability of a pair of parents is a function of their age-type (young, middle-aged, old, etc.) and is obtained using a fuzzy rule base and possibility theory. A fuzzy possibility/necessity based evolution process is proposed to deal with fuzzy objective function.

Suggested Citation

  • Partha Guchhait & Pravash Kumar Giri & Manas Kumar Maiti & Manoranjan Maiti, 2012. "Inventory Policy with Stock, Price and Credit-Linked Demand: A Fuzzy Genetic Algorithm Approach," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 3(2), pages 47-65, April.
    • Handle: RePEc:igg:jsds00:v:3:y:2012:i:2:p:47-65
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