Implementation of Dijkstra Algorithm and Multi-Criteria Decision-Making for Optimal Route Distribution

Nowadays, product distribution is extremely complex. The decision makers have many parameters to make an optimum decision. They avoid a receiving which is not on time. The aims to grant the best service. Mostly, the consideration parameters for decision-making are a cost and a distance. The paramete...

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Vydané v:Procedia computer science Ročník 161; s. 378 - 385
Hlavní autori: Rosita, Yesy Diah, Rosyida, Erly Ekayanti, Rudiyanto, Muhammad Adik
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 2019
Predmet:
Dijkstra
distribution
mcdm
priority
routing
routing
distribution
mcdm
priority
Dijkstra
ISSN:1877-0509, 1877-0509
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Shrnutí:Nowadays, product distribution is extremely complex. The decision makers have many parameters to make an optimum decision. They avoid a receiving which is not on time. The aims to grant the best service. Mostly, the consideration parameters for decision-making are a cost and a distance. The parameters are used to obtain an optimal route distribution. Nevertheless, there are other parameters which have also the priority level such as congestion and risk. Absolutely, the parameters have the priority level for a decision maker. Therefore, the making decisions is increasingly difficult by reason of many parameters and its priority level. In this research, the various parameters will be created into a value to facilitate a making decision of a distribution optimal route. Giving the priority level of all parameters has been employed to solve the problem by vector normalized technique that is the best-normalized technique of MCDM. The normalization is not only required to find the optimal route but also the system utilizes the priority level and Dijkstra algorithm which is the mostly method for the problem. Accordingly, the experimental result establishes that our system yielded high accuracy by considering all priority level of predetermined parameters.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2019.11.136