Forecast horizon of dynamic lot size model for perishable inventory with minimum order quantities

Jing, Fuying; Lan, Zirui; Yang, Ping

doi:10.3934/jimo.2019010

Cited by 4 publications

(2 citation statements)

References 51 publications

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“…Krommyda et al (2015) extended the work of Drezner et al (1995) by assuming the substitution rate between 0 to 1. Jing et al (2019) investigated the dynamic lot size problem for perishable stock by considering rate of deterioration and inventory cost as age dependent. Jing and Mu (2020) developed a dynamic programming algorithm that addressed the dynamic lot-sizing problem under storage capacity constraints with perishable products and demand substitution.…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainable optimal ordering quantity for non-instantaneous deteriorating items under joint replenishment with substitution and carbon emission

Singh

Mishra

2021

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Purpose Carbon emission is a significant issue for the current business market and global warming. Nowadays, most countries have focused to reduce the environmental impact of business with durable financial benefits. The purpose of this study is to optimize the entire cost functions with carbon emission and to find the sustainable optimal ordering quantity for retailers. Design/methodology/approach This paper illustrates a sustainable inventory model having a set of two non-instantaneous substitutable deteriorating items under joint replenishment with carbon emission. In this model demand and deterioration rate are considered as deterministic, constant and triangular fuzzy numbers. The objective is to find the optimal ordering quantity for retailers and to minimize the total cost function per unit time with carbon emission. The model is then solved with the help of Maple software. Findings This paper presents a solution method and also develop an algorithm to determine the order quantities which optimize the total cost function. A numerical experiment illustrates the improvement in optimal total cost of the inventory model with substitution over without substitution. The graphical results show the convexity of the cost function. Finally, sensitivity analysis is given to get the impact of parameters and validity of the model. Originality/value This study considers a set of two non-instantaneous substitutable deteriorating items under joint replenishment with carbon emission. From the literature review, in the authors’ knowledge no researcher has undergone this kind of study.

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Section: Literature Reviewmentioning

confidence: 99%

Sustainable optimal ordering quantity for non-instantaneous deteriorating items under joint replenishment with substitution and carbon emission

Singh

Mishra

2021

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“…Berk and Gürler [8] analyze (Q, r) inventory strategy and develop heuristics by considering fixed order cost and positive lead time. Jing et al [30] aim to determine the dynamic lot sizes for perishable inventory under minimum order quantities considering age-dependent stock deterioration rates and inventory costs. Minner and Transchel [37] analyze inventory management of perishable products considering different characteristics and service levels, and they offer dynamic ordering strategies different than (s, S) and compare these strategies with the (s, S) strategy.…”

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Pricing and lot-sizing decisions for perishable products when demand changes by freshness

Kaya¹,

Bayer²

2021

JIMO

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Perishable products like dairy products, vegetables, fruits, pharmaceuticals, etc. lose their freshness over time and become completely obsolete after a certain period. Customers generally prefer the fresh products over aged ones, leading the perishable products to have a decreasing demand function with respect to their age. We analyze the inventory management and pricing decisions for these products, considering an age-and-price-dependent stochastic demand function. A stochastic dynamic programming model is developed in order to decide when and how much inventory to order and how to price these products considering their freshness over time. We prove the characteristics of the optimal solution of the developed model and extract managerial insights regarding the optimal inventory and pricing strategies. The numerical studies show that dynamic pricing can lead to significant savings over static pricing under certain parameter settings. In addition, longer replenishment cycles are seen under dynamic pricing compared to static pricing, even though similar quantities are ordered in each replenishment.

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A dynamic lot size model with perishable inventory and stockout

Jing

Chao

2021

Omega

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Forecast horizon of dynamic lot size model for perishable inventory with minimum order quantities

Cited by 4 publications

References 51 publications

Sustainable optimal ordering quantity for non-instantaneous deteriorating items under joint replenishment with substitution and carbon emission

Sustainable optimal ordering quantity for non-instantaneous deteriorating items under joint replenishment with substitution and carbon emission

Pricing and lot-sizing decisions for perishable products when demand changes by freshness

A dynamic lot size model with perishable inventory and stockout

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