A modified of FR method to solve unconstrained optimization

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

doi:10.1088/1742-6596/1804/1/012023

Cited by 22 publications

(6 citation statements)

References 7 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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“…There are two types of graphs either simple or complex so that larger graphs contain more nodes and many other possibilities of sub graph can reach millions or billions making them, which is very difficult to get a MST [14,15]. In addition, the lengths are usually have different weights, that is one edge can be give 8 weight and a length of 5 meters while another edge of the same length can give 6 weights.…”

Section: Finding the Mstmentioning

confidence: 99%

Optimizing the minimum spanning tree (MST) and its relationship with the minimum cut

Kafaji¹,

Shiker²

2022

ijhs

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The ST ST is a sub-tree of the original network so that the network graph can contain more than one sub-tree that reaches all the vertices of the network and the minimum spanning tree MST is the smallest measure among all the weights of the sub-spanning trees. To get the MST in a simplified way the Kruskal algorithm and the prime algorithm have been applied to several examples. In this work, we applied the new technique to the same examples, and the results were equal or have less value comparing with the above algorithms. The main idea of this technique is to link between the subject of the MST and the subject of the minimum cutoff, so that all the paths of the original graph were extracted and we calculated the weight of each path and chose the path that carried the largest weight, then we can grade by taking the paths according to need from largest to smallest and we cut the edge with the largest weight from that path and continue this process until the conditions of the ST are met.

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A modified of FR method to solve unconstrained optimization

Cited by 22 publications

References 7 publications

Manage warehousing goods and funds flows

Manage warehousing goods and funds flows

Improvement time estimate of network optimization

Optimizing the minimum spanning tree (MST) and its relationship with the minimum cut

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