COMPARATIVE STUDY OF ANTS COLONY ALGORITHM AND GENETIC ALGORITHM FOR OPTIMAL ROUTING (CASE STUDY: PARSABAD TOWN AND SUBURBS, IRAN

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KHAMMAR GHOLAMALI; PASBAN ISALOU VAHID; MOGHGAN NEGARH

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Journal: Journal of Transportation Engineering Year:2017 | Volume:8 | Issue:3 Page(s): 389-404

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Title

COMPARATIVE STUDY OF ANTS COLONY ALGORITHM AND GENETIC ALGORITHM FOR OPTIMAL ROUTING (CASE STUDY: PARSABAD TOWN AND SUBURBS, IRAN

Author(s)

KHAMMAR GHOLAMALI | PASBAN ISALOU VAHID | MOGHGAN NEGARH | Issue Writer Certificate

Keywords

ANT COLONY ALGORITHMQ1

GENETIC ALGORITHMQ2

PARSABAD (IRAN)Q1

AMBULANCEQ1

ROUTINGQ2

Abstract

Promptness of relief groups and especially, of inter- cities AMBULANCEs has a vital role in their performance during unpredicted disasters. In this regard, optimal ROUTING of these groups seems necessary in order to cover maximum population centers. For this purpose, the use of artificial intelligence and the so-called “new ROUTING algorithms, ” and its localization among inter/ intra- cities sections, based on their extent and spread, can be an efficient way for efficient urban management and relief organization. Therefore, the aim of this study was to show the practical application of ANT COLONY ALGORITHM for optimizing ROUTING and minimizing the travelled distance. Ultimately, to demonstrate the capabilities of this algorithm, it was compared with the GENETIC ALGORITHM. In this research, the case study was performed on over 29 urban and rural points, originated in Parsabad city, in MATLAB and shown in the GIS environment. The proposed model in this paper can not only be used to analyze the issue, but it also can be used to optimize the ROUTING of distribution of basic goods in cases of natural and human disasters, traffic problem, and so on. Need to note that in the proposed method, the Rolette wheel Selection method is used for random selection of the neighborhoods. The results showed that due to the limited area of the case study, time and quality of achieving to optimal route in ANT COLONY ALGORITHM were calculated 0.19 ms faster than the genetic theory, whereas, given the movement of 30 ants, the time required to arrive to the scene by the AMBULANCEs for ANT COLONY ALGORITHM and the GENETIC ALGORITHM was calculated 19' 45' ' and 24' 15' ', respectively.

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APA: Copy

KHAMMAR, GHOLAMALI, PASBAN ISALOU, VAHID, & MOGHGAN, NEGARH. (2017). COMPARATIVE STUDY OF ANTS COLONY ALGORITHM AND GENETIC ALGORITHM FOR OPTIMAL ROUTING (CASE STUDY: PARSABAD TOWN AND SUBURBS, IRAN. JOURNAL OF TRANSPORTATION ENGINEERING, 8(3 ), 389-404. SID. https://sid.ir/paper/224030/en

Vancouver: Copy

KHAMMAR GHOLAMALI, PASBAN ISALOU VAHID, MOGHGAN NEGARH. COMPARATIVE STUDY OF ANTS COLONY ALGORITHM AND GENETIC ALGORITHM FOR OPTIMAL ROUTING (CASE STUDY: PARSABAD TOWN AND SUBURBS, IRAN. JOURNAL OF TRANSPORTATION ENGINEERING[Internet]. 2017;8(3 ):389-404. Available from: https://sid.ir/paper/224030/en

IEEE: Copy

GHOLAMALI KHAMMAR, VAHID PASBAN ISALOU, and NEGARH MOGHGAN, “COMPARATIVE STUDY OF ANTS COLONY ALGORITHM AND GENETIC ALGORITHM FOR OPTIMAL ROUTING (CASE STUDY: PARSABAD TOWN AND SUBURBS, IRAN,” JOURNAL OF TRANSPORTATION ENGINEERING, vol. 8, no. 3 , pp. 389–404, 2017, [Online]. Available: https://sid.ir/paper/224030/en

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