A Proposed Approach to Extend the Economic Order Quantity (EOQ) Model Using Discrete Event Simulation

Abstract

Abstract. The economic order quantity (EOQ) and the economic production quantity (EPQ) are well-known and commonly used inventory control techniques. The standard results are easy to apply but are based on a number of unrealistic assumptions. One of the assumption is that the demand is normally distributed in any interval. In several practical cases the assumption about independence of successive demands, and consequently demand normal distribution in any interval, is not supported by real data. This paper investigates the effects on the expected service level (SL) after relaxing normal distribution assumption on the demand. The present work shows a possible strategy to use classic inventory model, such as EOQ/EPQ model, adopting discrete event simulation analysis to quantify model performances under relaxed assumptions.Keywords: EOQ, inventory techniques, discrete event, simulation analysis. IntroductionThe economic order quantity (EOQ), first introduced . The standard EOQ and economic production quantity (EPQ) results are easy to apply but are based on a number of unrealistic assumptions [6]. One of the assumption is that the demand is normally distributed in any interval, it is assumed that successive demands are independent and, consequently, the accumulated demand over many time units is approximately normal. The realization that inventories operate under less than ideal situations gives rise to a subset of inventory modeling theory that performs sensitivity analysis on models operating under stochastic conditions [7]. Several extensions of the classic EOQ/EPQ model have been, Borgonovo [8] presents a good review of them across several fields of research. A branch comprises models where the assumption that all units are of perfect quality is removed, for a deep literature review you can see Chan [9]. Another field of EOQ extended models is focused on deteriorating inventory models for perishables management, for a good review you can see Goyal [10] and Ferguson [11]. Some papers mixed the two proposals to develop a model that better

Regression analysis as an alternative method of determining the Economic Order Quantity and Reorder Point

“…At the same time, both the model itself and the possibility of using the optimization method with the use of a mathematical formula are criticized, because as some authors state they are based on of unrealistic assumptions. A simulation method is proposed as an alternative ( Davoli and Melloni, 2012 ). Obtained, thanks to the simulation methods may differ from the ones obtained from the classic EOQ ( Dellino et al., 2010 ; Shadkam and Bijari, 2017 ).…”

Strand Inventory Analysis of Post Tension in PT XYZ Using Discrete-Event Simulation Method

“…Thus, the discrete event simulation method can be utilized for inventory analysis in construction companies, as this method can help expand classical models with more realistic assumptions. (Davoli & Melloni, 2012). This research is a continuation of the study that has been conducted by Milewski & Wiśniewski (2022) regarding the simplification of complex relationships between determining the quantity of shipments that will affect shipping costs, inventory costs, and warehousing costs, along with the potential for lost sales if adjustments are made, using simulation methods.…”