Analysis and optimisation of inventory management policies for perishable food products: a simulation study

Bottani, Eleonora; Ferretti, Gino; Montanari, Roberto; Rinaldi, Marta

doi:10.1504/ijspm.2014.061429

Cited by 24 publications

(8 citation statements)

References 29 publications

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“…The optimal setting will be identified by varying the operating leverages of the reorder policy (i.e., lot size and OP) within the respective ranges (according to Table 1) and by computing, for each couple of values, the total cost of the inventory policy. In line with the published literature (Kang and Gershwin, 2004;Hardgrave, 2009;Bottani and Montanari, 2010;Bottani et al, 2014), the total cost of inventory management in presence of inaccuracies consists of several cost components, namely:…”

Section: Simulation Step 1 -Minimum Cost Configuration Without Inaccumentioning

confidence: 76%

“…The final customer's demand is modelled as a stochastic variable, with uniform distribution ranging from 900 to 3,200 pallets/day (μ = 2,050 and σ = 665 pallets/day), which are typical values for the shipment of a single product from a manufacturer's distribution centre to its customers (see Bottani and Rizzi, 2008). Some examples related to the simulation of a reorder process under Microsoft Excel™ can be found in Montanari (2010, 2011) or Bottani et al (2007Bottani et al ( , 2012Bottani et al ( , 2013Bottani et al ( , 2014.…”

Section: Simulation Model and Input Datamentioning

confidence: 99%

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Inventory management in the presence of inventory inaccuracies: an economic analysis by discrete-event simulation

Bottani

Mantovani

Montanari

et al. 2017

IJSCIM

Self Cite

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Today, inventory management is almost entirely based on information systems. However, inventory records can always be prone to errors, leading to underestimated or overestimated inventory. In this study, the effect generated by inventory record inaccuracies on the economic performance of a warehouse of fast moving consumer goods is analysed. A simulation model is developed under Microsoft Excel™ to reproduce the inbound and outbound flows of product at the warehouse, together with the generation of errors in these flows. Different types of errors, correction mechanisms and reorder policies are taken into account in the analysis. As output, the simulation model returns the total cost of the inventory management as a function of the error level, the reorder policy and the correction mechanism adopted. The results of the study provide useful guidelines for warehouse managers. More specifically, outcomes can support strategic decisions, such as the choice among different correction mechanisms, the opportunity to adopt them (or not) or the opportunity to modify (or not) the operating leverages of the reorder policy to adapt them to the presence of errors in inventory records.

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Section: Simulation Step 1 -Minimum Cost Configuration Without Inaccumentioning

confidence: 76%

Section: Simulation Model and Input Datamentioning

confidence: 99%

Inventory management in the presence of inventory inaccuracies: an economic analysis by discrete-event simulation

Bottani

Mantovani

Montanari

et al. 2017

IJSCIM

Self Cite

View full text Add to dashboard Cite

show abstract

“…Both reviews classified models for deteriorating inventory according to product lifetime and demand characteristics; yet, both did not consider environmental implications of perishable inventory items. Traditional inventory policies were applied to perishable food products and simulation was used to find the optimal settings of the inventory models parameters while considering shelf-life constraints [11]. Simulation was also used in evaluating order policies in a supply chain of fresh produce and including costs to reflect losses in shelf life of products [12].…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainable Agri-Food Supply Chain with Uncertain Demand and Lead Time

Galal¹,

El-Kilany²

2016

Int. j. simul. model.

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Food supply, safety and quality have become major concerns worldwide. Agri-food supply chains (ASC) possess special characteristics due to the perishability of their products and the high uncertainty of supply and demand. Furthermore, different sources of CO 2 emissions exist in an ASC due to storage, transportation, and disposal of fresh produce. Thus to ensure the sustainability of the supply chain, planning decisions have to be made with consideration of both economic and environmental aspects. This work studies the effect of changing the order quantity in a two-echelon agri-food supply chain on costs, emissions, and service level. A discrete-event simulation model is developed to include stochastic demand and lead-time, the amount of CO 2 emissions along the supply chain, service levels, and product lifetime effects. Simulation results show that reducing the order quantities can reduce costs and emissions by 27.42 % and 18.21 %; respectively, without sacrificing high service levels. Also, relying on costs or service level as sole objectives of the supply chain without consideration of emissions can result in greater economic and environmental inefficiencies in management of inventory levels.

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“…The assumption of the traditional EOQ model has been changed from "goods are nondegenerative" to "goods are degenerative goods (e.g., petroleum and other volatile products) that decrease in volume over time even when unsold" [33][34][35][36]. Since 2010, an increasing number of studies on deteriorating goods inventory have focused on fresh (perishable) goods whose quality deteriorates over time [25,[37][38][39][40][41][42][43][44][45][46][47][48].…”

Section: Introductionmentioning

confidence: 99%

Economic Order Quality Model for Determining the Sales Prices of Fresh Goods at Various Points in Time

Chen

2017

Journal of Food Quality

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Although the safe consumption of goods such as food products, medicine, and vaccines is related to their freshness, consumers frequently understand less than suppliers about the freshness of goods when they purchase them. Because of this lack of information, apart from sales prices, consumers refer only to the manufacturing and expiration dates when deciding whether to purchase and how many of these goods to buy. If dealers could determine the sales price at each point in time and customers' intention to buy goods of varying freshness, then dealers could set an optimal inventory cycle and allocate a weekly sales price for each point in time, thereby maximizing the profit per unit time. Therefore, in this study, an economic order quality model was established to enable discussion of the optimal control of sales prices. The technique for identifying the optimal solution for the model was determined, the characteristics of the optimal solution were demonstrated, and the implications of the solution's sensitivity analysis were explained.

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Analysis and optimisation of inventory management policies for perishable food products: a simulation study

Cited by 24 publications

References 29 publications

Inventory management in the presence of inventory inaccuracies: an economic analysis by discrete-event simulation

Inventory management in the presence of inventory inaccuracies: an economic analysis by discrete-event simulation

Sustainable Agri-Food Supply Chain with Uncertain Demand and Lead Time

Economic Order Quality Model for Determining the Sales Prices of Fresh Goods at Various Points in Time

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