Order quantities for perishable inventory control with non-stationary demand and a fill rate constraint

Pauls-Worm, K.G.J.; Hendrix, E.M.T.; Alcoba, Alejandro G.; Haijema, R.

doi:10.1016/j.ijpe.2015.10.009

Cited by 40 publications

(24 citation statements)

References 14 publications

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“…Among non-financial measures, fill rate (FR) is the most common measure. FR increases as demand uncertainty decreases [25,26].…”

Section: The Effects Of Consumer Demandmentioning

confidence: 98%

“…Second, there is a lack of models that investigate the effects of consumer demand for a multi-echelon supply chain model. The effects of consumer demand have been investigated for a single-product single-echelon model [25], or for a two-echelon model but focused only on the manufacturer, not the supplier [26]. These two models support an investigation of the effects of consumer demand on an echelon of the supply chain.…”

Section: The Effects Of Consumer Demandmentioning

confidence: 99%

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Effects of Consumer Demand, Product Lifetime, and Substitution Ratio on Perishable Inventory Management

2018

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With the intensification of global population, food security is a big concern. Food waste stems from inappropriate inventory management. Companies offer a wide range of products to capture more sales, yet this increases inventories and complicates inventory management. Management challenges are worsened by three factors: uncertain consumer demand, product lifetimes, and consumer substitution among the product range. This research aims to understand the effects of these factors on inventory performance. The analytic hierarchy process (AHP) method was used to weight the importance of each of the non-financial performance measures from the simulation results and data envelopment analysis (DEA) was used to rank and evaluate the scenarios. Then, the most favorable scenario or replenishment policy, which had the lowest DEA efficiency score, was chosen. The results show that when the substitution ratio is greater, its interaction with consumer demand and product lifetime has mostly a small-or medium-sized effect on retailers' performance, in contrast to relatively larger effects on the supplier. These findings show that suppliers' performance is affected largely by the existence of the bullwhip effect in the model. Recommendations are provided for managers who are facing uncertainties of consumer demand, substitution, and product lifetime.

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“…Among non-financial measures, fill rate (FR) is the most common measure. FR increases as demand uncertainty decreases [25,26].…”

Section: The Effects Of Consumer Demandmentioning

confidence: 98%

Section: The Effects Of Consumer Demandmentioning

confidence: 99%

Effects of Consumer Demand, Product Lifetime, and Substitution Ratio on Perishable Inventory Management

2018

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“…The study ignores preparation costs and calculates safety inventories based on storage costs and lost sales costs, like prosed by this work, but without considering the possibility of overtime and external storage. Pauls-Worm, Hendrix, Alcoba, and Haijema (2016) analyze the situation of perishable products with probabilistic demand and limited demand proportion met (defined arbitrarily, and not based on the relationship between storage and shortage costs), comparing an optimizing approach (mixed integer nonlinear programming) with an approximate approach (mixed integer linear programming). They conclude that linear approximation is adequate when ordering costs make appropriate a replenishment cycle for the next product life period.…”

Section: Literature Reviewmentioning

confidence: 99%

Aggregate planning for probabilistic demand with internal and external storage

Biazzi

2018

JOSCM

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This paper presents three approaches to support decision-making for production planning, sales and inventory problems. They work in a situation with: non-stationary probabilistic demand; production capacity in regular hours and overtime; shortage leads to lost sales; limited internal storage space; and ordering costs resulting from machine preparation are negligible. In the first approach, we consider the problem as linear and deterministic. In the second, safety inventories are used to fill a probabilistic demand, but the possibility of stockout is not considered. The third approach estimates shortage resulting from demand uncertainty. The last two approaches use iterative processes to re-estimate unit holding cost, which is the basis to calculate safety inventories in each period of the horizon. Using Microsoft Excel Solver, with linear programming and nonlinear search functions, a hypothetical example (but strongly based on real-life companies) and some scenarios permit concluding that developing more realistic and complex models may not provide significant benefits. KEYWORDS | Inventory, non-stationary probabilistic demand, aggregate production planning, sales and operations mathematical models, no ordering costs.

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“…They proposed a dynamic optimization model to maximize total profit by assigning a limited production capacity and setting a suitable sales price. Pauls-Worm et al (2015) performed an investigation on the practical decision problem of fresh food production with a long production lead time. Gupta and Mohanty (2015) introduced a technique to solve a multi-stage production planning problem by considering different objectives, which are conflicting with each other.…”

Section: Literature Reviewmentioning

confidence: 99%

A two-stage production planning model for perishable products under uncertainty

Jey¹,

Javanshir²,

Mohajeri³

2017

10.5267/j.uscm

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In this study, a multi-product, multi-period and non-linear programming model is developed for production planning problem where demand is under uncertainty. The proposed study is designed for a real-world case study of chemicals production factory with 1 production line and 2 manual and automatic technologies. In manual technology, workers are working with 3 amateur, typical and professional skills in 2 typical and overtime working. Automatic technology in this system has n machines in which the repairing and maintenance of the machineries are also included. This system has n products and the products are life-limited and with diversity. The primary goal is to propose a model for improvement of the production planning and minimization of the production system costs. The products in high volume and various types are produced and they are stored in bottles as the final products. For different production periods, the human forces capacities are considered and the level of employment or forces dismissal are considered. The production process is forwarding and backward process is not acceptable; that is, it is not allowable to rework in this system. Delivering final product from stockpiles to the retailers is conducted using vehicles with limited capacity. To solve the model in larger space and because of the complexity of the model, meta-heuristic algorithm is used. Finally, it is concluded that due to covering most of the assumptions in perishable products production, the proposed model is closer to the real-world circumstances and reduces costs in production systems.All rights reserved. Growing Science Ltd. 7

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Order quantities for perishable inventory control with non-stationary demand and a fill rate constraint

Cited by 40 publications

References 14 publications

Effects of Consumer Demand, Product Lifetime, and Substitution Ratio on Perishable Inventory Management

Effects of Consumer Demand, Product Lifetime, and Substitution Ratio on Perishable Inventory Management

Aggregate planning for probabilistic demand with internal and external storage

A two-stage production planning model for perishable products under uncertainty

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