A fuzzy simulation via contractive mapping genetic algorithm approach to an imprecise production inventory model under volume flexibility

A fuzzy simulation via contractive mapping genetic algorithm approach to an imprecise production inventory model under volume flexibility

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Article ID: iaor20132566
Volume: 7
Issue: 2
Start Page Number: 90
End Page Number: 100
Publication Date: May 2013
Journal: Journal of Simulation
Authors: , , ,
Keywords: heuristics: genetic algorithms, inventory
Abstract:

In this paper, an economic production quantity model for multi‐item with storage space and budget constraints in a volume flexible manufacturing system is developed. Here it is assumed that the demand rate is constant up to a certain level of stock and after that it depends on stock itself. The unit production cost is taken to be a function of the finite production rate involving labour cost and wear and tear expenditure. Here, the inventory costs, selling price, storage space and available budget are defined imprecisely. Using necessary measure theory, the imprecise problem is reduced to deterministic problem. Here, necessity measure approach has been used for triangle fuzzy number and parabolic fuzzy number. Finally the crisp nonlinear optimization problem is solved by Fuzzy simulation, Contractive Mapping Genetic Algorithm and Generalized Reduced Gradient technique. The model is illustrated numerically and the results are compared.

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