Nonlinear Conjugate Gradient Method with Modified Armijo Condition to Solve Unconstrained Optimization

Wasi, H. A.; Shiker, Mushtak A. K.

doi:10.1088/1742-6596/1818/1/012021

Cited by 23 publications

(6 citation statements)

References 6 publications

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“…The authors introduced many papers in different fields of sciences such as reliability [13][14][15][16][17][18][19][20][21][22] and optimization [23][24][25][26][27][28][29][30][31][32][33], but in this work we suggest a technique to reduce the cost and maintain the flow. Inventory is usually formed as a result of market conditions, supply and demand, or because it is affected by the general economic situation.…”

Section: Inventory Managementmentioning

confidence: 99%

Manage warehousing goods and funds flows

Kafaji¹,

Shiker²

2022

ijhs

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The cost of inventory management depends mainly on two basic units, the cost of keeping inventory and the cost of orders, as these two units, one complements the other. To show the total cost of inventory through laws, the authors suggested many techniques for this purpose. The cost of this operation gradually decreases with the use of its materials. In this work, the authors proposed some techniques in order to obtain the minimum cost by dividing the agreed period in three percentages after it was divided into two periods, meaning that the percentage of the costs paid by the company in the first part, middle part, and in last part of the period in order to reduce the cost as much as possible through several equations. That is we try to reduce the number of times that the goods are ordered to the minimum by increasing the number of units of goods in one order and to know the total inventory costs.

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Section: Inventory Managementmentioning

confidence: 99%

Manage warehousing goods and funds flows

Kafaji¹,

Shiker²

2022

ijhs

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“…The authors introduced many papers in various types of sciences such as optimization [14][15][16][17][18][19][20][21][22][23][24], operation research [25][26][27][28][29][30][31][32][33], and reliability [34][35][36][37][38][39][40][41][42][43], but in this work we propose a technique to improve the most likely estimate time for any project where we get less weight to estimate the time weighted of 2 instead of 4 for distributors while estimates of time pessimistic and optimistic weight of 1 because we see that giving weight 2 instead of 4 gives reasonable results, closer to reality, and appropriate degree of reliability. As well as to reduce the complete time of the project with achieve the desired goals and achieve results less than the estimated time obtained by the classic methods.…”

Section: Improvement Time Estimatementioning

confidence: 99%

Improvement time estimate of network optimization

Kafaji¹,

Shiker²

2022

ijhs

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It's known that the network is a graph that connects activities to points, as in every project the representation of activities and points varies, where the researchers previously assumed a weighted estimate of the time through a law in which they put the optimistic time estimate with the pessimistic time estimate with a weight of 1 and decided to give a greater weight to the weighted time estimate of 4, while in our current research it was proposed to improve the time estimate more likely and make it closer to reality with the achievement of the required results without any negative impact on the project, where the cost and time are reduced while the results are satisfactory, as we can give less weight to the weighted time estimate of 3 instead of 4 to estimate the potential time for distributors, while the pessimistic and optimistic time estimates remain the same with a weight of 1 for each of them.

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“…[4] The Trust region method together with BFGS update was used to solve the unconstrained optimization problem. [5] Introduced the new modified Armijo condition to solve unconstrained optimization problem. [6] modified the Powell Symmetric Broyden (MPSB ) update to guarantee the PD property of Hessian matrix where the original update does not guarantee this property.…”

Section: Introductionmentioning

confidence: 99%

Marquardt Extended Technique for Solving Unconstrained Optimization Problems

Mahmood

Eidi

Hassan

2022

J. Phys.: Conf. Ser.

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The objective of this article is to solve the unconstrained optimization problem by using Marquardt method together with MQ-N (modified quasi-Newton) method. The Hessian matrix will be computed numerically by using modified Broyden-Flechert-Goldfarb-Shanno (BFGS) update ( H-version) after convert it to the B-version by using Sherman-Morisson-Woodburge (SMW) formula which guarantee the two important properties SPD (symmetric and positive definite), and hence the exact second derivative of OF (objective function) does not be needed to compute. The line search technique is very important to accelerate the method to terminate at the minimum value of OF, so in this article the line search technique is instead by used the search technique of Marquardt method together with MQ-N method (especially modified BFGS method where the step size is equal one) to solve the unconstrained optimization problem. Test problems are solved by Matlab software to prove the effective of this new technique so called the Marquardt extended technique (MET).

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Nonlinear Conjugate Gradient Method with Modified Armijo Condition to Solve Unconstrained Optimization

Cited by 23 publications

References 6 publications

Manage warehousing goods and funds flows

Manage warehousing goods and funds flows

Improvement time estimate of network optimization

Marquardt Extended Technique for Solving Unconstrained Optimization Problems

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