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A fuzzy genetic algorithm with varying population size to solve an inventory model with credit-linked promotional demand in an imprecise planning horizon

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  • Kumar Maiti, Manas

Abstract

A genetic algorithm (GA) with varying population size is developed where crossover probability is a function of parents' age-type (young, middle-aged, old, etc.) and is obtained using a fuzzy rule base and possibility theory. It is an improved GA where a subset of better children is included with the parent population for next generation and size of this subset is a percentage of the size of its parent set. This GA is used to make managerial decision for an inventory model of a newly launched product. It is assumed that lifetime of the product is finite and imprecise (fuzzy) in nature. Here wholesaler/producer offers a delay period of payment to its retailers to capture the market. Due to this facility retailer also offers a fixed credit-period to its customers for some cycles to boost the demand. During these cycles demand of the item increases with time at a decreasing rate depending upon the duration of customers' credit-period. Models are formulated for both the crisp and fuzzy inventory parameters to maximize the present value of total possible profit from the whole planning horizon under inflation and time value of money. Fuzzy models are transferred to deterministic ones following possibility/necessity measure on fuzzy goal and necessity measure on imprecise constraints. Finally optimal decision is made using above mentioned GA. Performance of the proposed GA on the model with respect to some other GAs are compared.

Suggested Citation

  • Kumar Maiti, Manas, 2011. "A fuzzy genetic algorithm with varying population size to solve an inventory model with credit-linked promotional demand in an imprecise planning horizon," European Journal of Operational Research, Elsevier, vol. 213(1), pages 96-106, August.
    • Handle: RePEc:eee:ejores:v:213:y:2011:i:1:p:96-106
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    References listed on IDEAS

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    1. Jaggi, Chandra K. & Goyal, S.K. & Goel, S.K., 2008. "Retailer's optimal replenishment decisions with credit-linked demand under permissible delay in payments," European Journal of Operational Research, Elsevier, vol. 190(1), pages 130-135, October.
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    7. Wee, Hui-Ming & Lo, Chien-Chung & Hsu, Ping-Hui, 2009. "A multi-objective joint replenishment inventory model of deteriorated items in a fuzzy environment," European Journal of Operational Research, Elsevier, vol. 197(2), pages 620-631, September.
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    1. Prasenjit Pramanik & Manas Kumar Maiti & Manoranjan Maiti, 2018. "An appropriate business strategy for a sale item," OPSEARCH, Springer;Operational Research Society of India, vol. 55(1), pages 85-106, March.
    2. Majumder, Pinki & Mondal, Sankar Prasad & Bera, Uttam Kumar & Maiti, Manoranjan, 2016. "Application of Generalized Hukuhara derivative approach in an economic production quantity model with partial trade credit policy under fuzzy environment," Operations Research Perspectives, Elsevier, vol. 3(C), pages 77-91.
    3. K. F. Mary Latha & R. Uthayakumar, 2017. "A two-echelon supply chain coordination with quantity discount incentive for fixed lifetime product in a fuzzy environment," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1194-1208, November.
    4. Guchhait, Partha & Kumar Maiti, Manas & Maiti, Manoranjan, 2013. "Production-inventory models for a damageable item with variable demands and inventory costs in an imperfect production process," International Journal of Production Economics, Elsevier, vol. 144(1), pages 180-188.
    5. Chakrabortty, Susovan & Pal, Madhumangal & Nayak, Prasun Kumar, 2013. "Intuitionistic fuzzy optimization technique for Pareto optimal solution of manufacturing inventory models with shortages," European Journal of Operational Research, Elsevier, vol. 228(2), pages 381-387.
    6. Nita Shah, 2015. "Retailer’s replenishment and credit policies for deteriorating inventory under credit period-dependent demand and bad-debt loss," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(1), pages 298-312, April.

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