A genetic algorithm approach to optimize a multi-products EPQ model with discrete delivery orders and constrained space

Pasandideh, Seyed Hamid Reza; Niaki, Seyed Taghi Akhavan

doi:10.1016/j.amc.2007.05.007

Cited by 48 publications

(31 citation statements)

References 11 publications

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“…This same experience indicates that what managers accurately know is the set of constraints that have to be considered to manage inventories. The literature also supports that space and other physical resources limit the capacity to store items (Choi and Noble 2000;Gholami-Qadikolaei, Mirzazadeh, and Tavakkoli-Moghaddam 2015;Pasandideh and Niaki 2008;Pasandideh, Niaki, and Nia 2011), and monetary limitations constrain the value of inventories to be stocked (Bera et al 2009;Gholami-Qadikolaei, Mirzazadeh, and Tavakkoli-Moghaddam 2015;Schrady and Choe 1971). Similar constraints apply to set-up; for instance, the number of orders that can be launched per year (Muckstadt and Sapra 2010).…”

Section: Introductionmentioning

confidence: 92%

A practical model for managing inventories with unknown costs and a budget constraint

Vidal-Carreras

García-Sabater

2016

International Journal of Production Research

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The economic production quantity method is one of the simplest models to control production and inventory. However, the assumptions on which it is based make its application difficult in practical situations. In most companies, set-up and inventory costs are unknown, or may not even exist as such, although other data are known, such as available capacity in machining hours and limits set by the financing subsystem. The present work offers a multi-item inventory model that sets reference values using known values such as inventory investment limits and production capacity. In order to confer the proposed model's larger practical content, a spreadsheet available to be downloaded has been implemented. Finally, the model dynamics is illustrated as a numerical example obtained from a real company.

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Section: Introductionmentioning

confidence: 92%

A practical model for managing inventories with unknown costs and a budget constraint

Vidal-Carreras

García-Sabater

2016

International Journal of Production Research

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“…In this paper, we extend Pasandideh and Niaki [20] model to include shortages. We assume that all shortages are completely backordered.…”

Section: Introduction and Literature Reviewmentioning

confidence: 96%

“…Pasandideh and Niaki [20] developed a multi-product EPQ model with limited warehouse space. They assumed that the orders may be delivered discretely in the form of multiple pallets.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

A parameter-tuned genetic algorithm for multi-product economic production quantity model with space constraint, discrete delivery orders and shortages

Pasandideh

Niaki

Yeganeh

2010

Advances in Engineering Software

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“…In recent years, many efficient methods for determining the optimal solution to the multi-item multi constraints lot-sizing problem exist in the inventory literature. Pasandideh and Niaki [31] explored the assumptions of warehouse space limitation, discrete delivery policy, and equal delivery quantities in a multiitem inventory problem. This problem is formulated as a nonlinear integer programming model and a GA method is suggested in order to solve this model.…”

Section: Introductionmentioning

confidence: 99%

An analysis of multi-item inventory model using particle swarm optimization under discrete delivery orders and limited storage space

Öztürk

Şenel

2019

ijisae

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This study explores an economic production quantity (EPQ) model designed with the assumptions of discrete delivery orders and storage capacity constraints for a multi-item production inventory system. The main purpose of this study is to determine the optimal order quantity, the optimal number of deliveries and the optimal delivery quantity. First, the developed model as part of this study is analyzed using Genetic Algorithm (GA). Numerical analysis results are compared with those of previous studies and it was found that it is possible to have better results with an increasing number of iteration. The same model is then analyzed using Particle Swarm Optimization (PSO) algorithm. A comparison of the optimization methods showed that PSO gives better results over the GA under the same number of iterations and using the same population. The effects of important model parameters such as number of iterations, population, crossover, mutation rate on the optimal solution are analyzed. The results showed that PSO performs better than the GA with respect to the total cost and the total runtime as the solution of the problem in question.

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A genetic algorithm approach to optimize a multi-products EPQ model with discrete delivery orders and constrained space

Cited by 48 publications

References 11 publications

A practical model for managing inventories with unknown costs and a budget constraint

A practical model for managing inventories with unknown costs and a budget constraint

A parameter-tuned genetic algorithm for multi-product economic production quantity model with space constraint, discrete delivery orders and shortages

An analysis of multi-item inventory model using particle swarm optimization under discrete delivery orders and limited storage space

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