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Multi-Period EOQ Model for Multi-Generation Technology Products With Short Product Life Cycles

Multi-Period EOQ Model for Multi-Generation Technology Products With Short Product Life Cycles

Gaurav Nagpal, Udayan Chanda, Naga Vamsi Krishna Jasti, Sachin Gupta
Copyright: © 2022 |Volume: 14 |Issue: 1 |Pages: 22
ISSN: 1937-9633|EISSN: 1937-9641|EISBN13: 9781683180586|DOI: 10.4018/IJEA.306241
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MLA

Nagpal, Gaurav, et al. "Multi-Period EOQ Model for Multi-Generation Technology Products With Short Product Life Cycles." IJEA vol.14, no.1 2022: pp.1-22. http://doi.org/10.4018/IJEA.306241

APA

Nagpal, G., Chanda, U., Jasti, N. V., & Gupta, S. (2022). Multi-Period EOQ Model for Multi-Generation Technology Products With Short Product Life Cycles. International Journal of E-Adoption (IJEA), 14(1), 1-22. http://doi.org/10.4018/IJEA.306241

Chicago

Nagpal, Gaurav, et al. "Multi-Period EOQ Model for Multi-Generation Technology Products With Short Product Life Cycles," International Journal of E-Adoption (IJEA) 14, no.1: 1-22. http://doi.org/10.4018/IJEA.306241

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Abstract

In this paper, the multi-period EOQ model is developed for the technology products that have multiple generations co-existing in the market, with each of them having a very short product life cycle. The paper first develops the framework for computation of inventory-related costs and then minimizes the total replenishment costs using random search technique and approximating the non-linear expressions while using Simpson’s Rule for integration. The paper also provides numerical illustrations and establishes a few important theorems that relate the EOQ to the innovation of diffusions. It is found that the total replenishment cost curve, drawn on the EOQ axis in the case of technology generations is convex to the origin. Since the objective function is highly non-linear, the genetic algorithm has been used to find the solution to the problem. The study also suggests that the faster diffusion of the next generations has a conflicting effect on the EOQ of the first generation in the case of pooled and non-pooled logistics.

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