Optimal strategy for an inventory model based on agile manufacturing under imperfect production process

Dem, Himani; Singh, S.R.; Parasher, Leena

doi:10.1504/ijmor.2019.096981

Cited by 2 publications

(1 citation statement)

References 20 publications

(20 reference statements)

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“…They checked some fuzzy inventory models considering output and degradation, separating types of inventory models, respectively, into some classifications. Some important mathematical models based on EOQ models were developed (Dem et al, 2019;Dem et al, 2014;Malik et al, 2008;Mathur et al, 2019). Khan et al (2011) researched papers that broadened Salameh and Jaber's inventory model (Salameh and Jaber, 2000) in a bubbling setting.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Neuro-Optimization Techniques for Inventory Models in Manufacturing Sectors

Tyagi

Kumar²,

Malik

et al. 2022

JCCE

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Inventory modeling or policies are the necessity of every business or a new oil for any industry. In other words, inventory control and management are needed by businessmen or entrepreneurs to make effective strategies, i.e., for making their business profitable. It becomes a lot and a lot of vital for enterprises within the real-life things like producing sector like industry, food trade, etc. Inventory issues common in producing, remanufacturing, and lots of helpful applications like pharmaceutical. An associate improvement model for internal control of circulation enterprises was established to minimize the typical total price in the unit time of the inventory system. As we have seen, lot of researchers have made several attempts in the previous decade for improving inventory control/inventory policies, but due to the dynamic nature of human beings, it is difficult to make perfect and unique inventory for all business sectors. So, in this study, we will use collected data (from several research works done by the researchers, questionnaires, interviews) and then will apply an artificial neural network (ANN) concept to provide an optimized solution. Finally, our model shows economical, correct results, which can be additionally helpful for the inventory researchers to seek out the acceptable technique for determining the economic order quantity systems or creating AN assumption for making new inventory policies. Hence, this study provides helpful algorithms, economical inventory models for producing sectors, and future analysis direction toward our planned work.

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Section: Literature Reviewmentioning

confidence: 99%

A Novel Neuro-Optimization Techniques for Inventory Models in Manufacturing Sectors

Tyagi

Kumar²,

Malik

et al. 2022

JCCE

View full text Add to dashboard Cite

show abstract

An inventory model for a three-stage supply chain with random capacities considering disruptions and supplier reliability

et al. 2020

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This study develops an inventory model to solve the problems of supply uncertainty in response to demand which follows a Poisson distribution. A positive aspect of this model is the consideration of random inventory, delivery capacities and supplier's reliability. Additionally, we assume supplier capacity follows an exponential distribution. This inventory model addresses the problem of a manufacturer having an imperfect production system with single supplier and single retailer and considers the quantity of product (Q), reorder points (r) and reliability factors (n) as the decision variables. The main contribution of our study is that we consider supplier may not be able to deliver the exact amount all the time a manufacturer needed. We also consider that the demand and the time interval between successive availability and unavailability of supplier and retailer follows a probability distribution. We use a genetic algorithm to find the optimal solution and compare the results with those obtained from simulated annealing algorithm. Findings reveal the optimal value of the decision variables to maximize the average profit in each cycle. Moreover, a sensitivity analysis was carried out to increase the understanding of the developed model. The methodology used in this study will help manufacturers to have a better understanding of the situation through the joint consideration of disruption of both the supplier and retailer integrated with random capacity and reliability.

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Optimal strategy for an inventory model based on agile manufacturing under imperfect production process

Cited by 2 publications

References 20 publications

A Novel Neuro-Optimization Techniques for Inventory Models in Manufacturing Sectors

A Novel Neuro-Optimization Techniques for Inventory Models in Manufacturing Sectors

An inventory model for a three-stage supply chain with random capacities considering disruptions and supplier reliability

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