Development of multi-item EOQ when the constraints of investment and storage capacity are active

Ghafour, Karzan Mahdi; Ramli, Razamin; Zaibidi, Nerda Zura

doi:10.1063/1.4937024

Cited by 5 publications

(6 citation statements)

References 11 publications

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“…is used to model the extended search control (exploration) for each iteration. The average value of the solution location at iteration t is called 𝑋𝑀(𝑡), which can be obtained using Equation (18). The current and maximum iteration symbols are t and T, and a rand is a random number between (0, 1).…”

Section: Aquila Algorithmmentioning

confidence: 99%

Optimization Multi-Item Lot Sizing Model involve Transportation and Capacity Constraint under Stochastic Demand using Aquila Optimizer

Utama,

Rubiyanti,

Wardana

2023

JTI

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Inventory issues are often a major concern as they significantly impact operating costs. Lot sizing is one of the key decisions in managing inventory. However, in a real context, the demand for each item is often uncertain. It is supplied from the same supplier, requiring product orders to be placed in the same period. In addition, limited vehicle capacity and transportation costs are important factors to consider in making multi-item lot sizing decisions. The purpose of this study is to propose a new inventory model multi-item lot sizing model involving transportation cost and capacity constraints under stochastic demand. The decision variables involved in the model are each item's ordering cycle and safety factor with the objective function of minimizing the total inventory cost. To optimize the inventory model, this study also offers the advanced procedure of the Aquila Algorithm. This study also presents sensitivity analysis to the appropriate policy for optimizing the multi-item lot-sizing inventory problem involving transportation cost and capacity constraint under stochastic demand.

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Section: Aquila Algorithmmentioning

confidence: 99%

Optimization Multi-Item Lot Sizing Model involve Transportation and Capacity Constraint under Stochastic Demand using Aquila Optimizer

Utama,

Rubiyanti,

Wardana

2023

JTI

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“…Example: To illustrate the result of above theory, we used our previous example in (Ghafour et al, 2015).The parameters illustrate the concept of first model with total annual number of orders. However, Table 1 shows all the parameters of the model with total allowed number of orders is equal to 7.…”

Section: Numerical Examplementioning

confidence: 99%

“…This condition can be achieved when the left hand side of the constraint is not satisfy the right hand side, in another interpretation, the left hand side is greater than the right hand side which mean the constraint is active. However, in a previous work we developed a new formula of EOQ in multi-items when the objective function is subjected to investment and capacity of shortage space constraints and we presented a numerical example to show the effect of the constraints on EOQ when it is active and the changes in the value of EOQ (Ghafour et al, 2015). Therefore, this paper is an extension of the paper aforementioned to establish a new formula of EOQ in the same deterministic inventory models (Purchases with Shortage and Production with Shortage) when the constraint of number of annual order is active.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Multi-Item EOQ when the Constraint of Annual Number of Orders is Active

Ghafour¹,

Rashid²

2016

MAS

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The responsibility in inventory models decides of how much or how many of inventory items to order. An economic order quantity (EOQ) differs from a model to another according to the assumptions and the variables. This paper has developed the EOQ in two deterministic inventory model (Purchases with shortage and production with shortage) of multi-item when the objective function is subjected to annual number of orders. The constraints are assumed to be active if the left hand side does not satisfy the right hand side condition. Thus, Lagrange method is used to find the new multi-item EOQ in each two models with the constraint to achieve the new formula of EOQ. Finally, a numerical example is provided to justify the proposed model.

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“…This additional constraint helps us to determine the minimum number of monthly orders where shortages is zero. For instance, a TVC was formulated in [25] by incorporating purchase with shortage and production with shortage. Contrary, our aim is to obtain the number of inventory orders that should be considered.…”

mentioning

confidence: 99%

Constrained Stochastic Inventory Control Models for Multi-Item with Variable Demand

Udoh

Ukpongessien

Iseh

2022

AJPAS

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Constrained multi-item inventory system with variable demands are considered. The demand rates of five selected multi-item - Cowbell, Milo, SMA, Cerelac and Golden Morn were modeled as Weibull, Normal and Lognormal probability distributions respectively with the aid of chi-squared multinomial goodness-of-fit test. The respective probability distributions with estimated location parameters: 491.55, 536.92, 10.5, 2.1926 and 5.3103 were used as the basis of probabilistic inventory models to obtain dynamic EOQ for each item under each constraint subject to Kuhn, Karush and Tucker (KKT) conditions as against the use of simple averages in deterministic inventory models. The optimal values of these constraints: available warehouse space (124sq.ft), specified level of inventory (94 units), limited capital (76,671.52 naira) and number of orders (1/month) were obtained using the optimal EOQ values to establish optimal inventory level and constraints level/capacity for each item in order to avoid shortage or excess stock.

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Development of multi-item EOQ when the constraints of investment and storage capacity are active

Cited by 5 publications

References 11 publications

Optimization Multi-Item Lot Sizing Model involve Transportation and Capacity Constraint under Stochastic Demand using Aquila Optimizer

Optimization Multi-Item Lot Sizing Model involve Transportation and Capacity Constraint under Stochastic Demand using Aquila Optimizer

Optimizing Multi-Item EOQ when the Constraint of Annual Number of Orders is Active

Constrained Stochastic Inventory Control Models for Multi-Item with Variable Demand

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