2018
DOI: 10.15294/sji.v5i1.13360
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Comparison of Dynamic Programming Algorithm and Greedy Algorithm on Integer Knapsack Problem in Freight Transportation

Abstract: At this time the delivery of goods to be familiar because the use of delivery of goods services greatly facilitate customers. PT Post Indonesia is one of the delivery of goods. On the delivery of goods, we often encounter the selection of goods which entered first into the transportation and  held from the delivery. At the time of the selection, there are Knapsack problems that require optimal selection of solutions. Knapsack is a place used as a means of storing or inserting an object. The purpose of this res… Show more

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Cited by 13 publications
(12 citation statements)
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References 14 publications
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“…The amount of labor required according to the analysis of the Dynamic Programming method with forward recursive and backward recursive calculations is the same, namely: 1) Morning shift = 105 people 2) Day shift = 104 people 3) Night shift = 104 people The number of workers generated through the calculation of the Dynamic Programming method is the allocation of labor that is estimated to be maximum and optimal who can work every day. If this calculation is applied to the production process, it will provide benefits for the company, where the labor can be allocated to each shift precisely according to the number of lens orders available [30,31]. Labor that can be used or worked every day at PT.…”
Section: Resultsmentioning
confidence: 99%
“…The amount of labor required according to the analysis of the Dynamic Programming method with forward recursive and backward recursive calculations is the same, namely: 1) Morning shift = 105 people 2) Day shift = 104 people 3) Night shift = 104 people The number of workers generated through the calculation of the Dynamic Programming method is the allocation of labor that is estimated to be maximum and optimal who can work every day. If this calculation is applied to the production process, it will provide benefits for the company, where the labor can be allocated to each shift precisely according to the number of lens orders available [30,31]. Labor that can be used or worked every day at PT.…”
Section: Resultsmentioning
confidence: 99%
“…Thus, greedy algorithms can provide a hypothesis that seems optimal at the time but does not guarantee a global optimization in the future. However, dynamic programming finds the optimal solution for the sub-problems and makes an informed choice to find the most optimal solution by combining the results of these sub-problems [ 32 ].…”
Section: Proposed Algorithm Based On Dynamic Programmingmentioning
confidence: 99%
“…In the admission of this year, there are 575 applicants who register via zone system and 218 applicants will be selected as candidate of new students of SMAN 12 Semarang. In order to solve the problem, dynamic programming is chosen since according to [5], dynamic programming algorithm has better performance in terms of the optimal solution than Greedy algorithm. Dynamic Programming is a mathematical technique used to optimize the decision-making process in phases.…”
Section: Analysis Of Needs and Data Collectionmentioning
confidence: 99%
“…In order to compute the value of 𝑧𝑧 𝑡𝑡 , consider the domain range of final score. Since the minimum and the maximum value of final score's domain range are 0 and 100 respectively, 𝑧𝑧 𝑡𝑡 can be computed by using equation ( 4) or (5). Now, reconsider the predicate of final score in the previous step.…”
Section: Defuzzificationmentioning
confidence: 99%
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