Optimizing the Carpool Service Problem with Genetic Algorithm in Service-Based Computing

Jiau, Ming-Kai; Huang, Shih-Chia; Lin, Chih-Hsian

doi:10.1109/scc.2013.56

Cited by 19 publications

(10 citation statements)

References 8 publications

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“…2. The chromosome coding is totally dynamic and does not need a decoding process to be exploited, unlike the coding of Herbawi and Weber 2 and Jiau et al 20 3. Unlike classic implementations of the evolutionary algorithm, where the initial solution is built randomly, our MACGeO algorithm starts by constructing a feasible initial solution that respects the capacity constraint.…”

Section: Our Motivationmentioning

confidence: 99%

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An evolutionary approach to solve the dynamic multihop ridematching problem

2016

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The multihop ridesharing system generates a ridematching solution with an arbitrary number of transfers that respects personal preferences of the users and their time constraints with detour willingness. As it is considered to be NP-complete, an efficient metaheuristic is required in the application to solve the dynamic multihop ridematching problem. In this context, a novel approach, called Metaheuristics Approach Based on Controlled Genetic Operators (MACGeO), which is supported by an original dynamic coding, is developed to address the multihop ridematching problem. The performance of the proposed approach is measured via simulation scenarios, which feature various numbers of carpool drivers (vehicles) and riders (passengers). Experimental results show that the multihop ridematching could greatly increase the number of matched requests while minimizing the number of vehicles required.

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Section: Our Motivationmentioning

confidence: 99%

“…The chromosome coding is totally dynamic and does not need a decoding process to be exploited, unlike the coding of Herbawi and Weber 2 and Jiau et al 20…”

Section: Related Workmentioning

confidence: 99%

An evolutionary approach to solve the dynamic multihop ridematching problem

2016

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“…It takes advantage of the cloud as an agency node station, where data generated from moving vehicles are processed and exchanged among themselves. Examples include smartphone-based communication applications, such as instant messaging subscription services, video-capturing VoIP calls, online carpool matching [17]- [19], etc.…”

Section: A Vehicles To Clouds (Vtc) Infrastructurementioning

confidence: 99%

Multimedia Services in Cloud-Based Vehicular Networks

Jiau

Huang

Hwang

et al. 2015

IEEE Intell. Transport. Syst. Mag.

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Research into the requirements for mobile services has seen a growing interest in the fields of cloud technology and vehicular applications. Integrating cloud computing and storage with vehicles is a way to increase accessibility to multimedia services, and inspire myriad potential applications and research topics. This paper presents an overview of the characteristics of cloud computing, IEEE IntEllIgEnt transportatIon systEms magazInE • 63 • fall 2015 and introduces the basic concepts of vehicular networks. An architecture for multimedia cloud computing is proposed to suit subscription service mechanisms. The tendency to equip vehicles with advanced and embedded devices such as diverse sensors increases the capabilities of vehicles to provide computation and collection of multimedia content in the form of the vehicular network. Then, the taxonomy of cloud-based vehicular networks is addressed from the standpoint of the service relationship between the cloud computing and vehicular networks. In this paper, we identify the main considerations and challenges for cloud based vehicular networks regarding multimedia services, and propose potential research directions to make multimedia services achievable. More specifically, we quantitatively evaluate the performance metrics of these researches. For example, in the proposed broadcast storm mitigation scheme for vehicular networks, the packet delivery ratio and the normalized throughput can both achieve about 90%, making the proposed scheme a useful candidate for multimedia data exchange. Moreover, in the video uplinking scenarios, the proposed scheme is favorably compared with two well-known schedulers, M-LWDF and EXP, with the performance much closer to the optimum.

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“…Vairuotojai paskelbia savo kelionės maršrutą, keliautojai paskelbia apie pageidaujamą kelionę, nurodydami norimą išvykimo laiką. Programa automatiškai suporuoja sistemos dalyvius, kiekvienai pusei, kuri keliauja tuo pačiu maršrutu, persiunčia informaciją (Jiau et al 2013).…”

Section: Kiti Automobilių Panaudojimo Ir Stovėjimo Vietų Mažinimo Būdaiunclassified

Lengvųjų automobilių stovėjimo aikštelių mieste vertinimas daugiatiksliais metodais

Palevičius¹

2014

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Mokslinis vadovas prof. dr. Marija BURINSKIENĖ (Vilniaus Gedimino technikos universitetas, statybos inžinerija-02T). Vilniaus Gedimino technikos universiteto Statybos inžinerijos mokslo krypties disertacijos gynimo taryba: Pirmininkas prof. dr. Donatas ČYGAS (Vilniaus Gedimino technikos universitetas, statybos inžinerija-02T). Nariai: dr. Raimondas BLIŪDŽIUS (Kauno technologijos universitetas, statybos inžinerija-02T), prof. habil. dr. Henrikas SIVILEVIČIUS (Vilniaus Gedimino technikos universitetas, transporto inžinerija-03T), prof. dr. Juris SMIRNOVS (Rygos technikos universitetas, statybos inžinerija-02T), prof. habil. dr. Leonas USTINOVIČIUS (Vilniaus Gedimino technikos universitetas, statybos inžinerija-02T). Disertacija bus ginama viešame Statybos inžinerijos mokslo krypties disertacijos gynimo tarybos posėdyje 2014 m. gruodžio 11 d. 10 val. Vilniaus Gedimino technikos universiteto senato posėdžių salėje.

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Optimizing the Carpool Service Problem with Genetic Algorithm in Service-Based Computing

Cited by 19 publications

References 8 publications

An evolutionary approach to solve the dynamic multihop ridematching problem

An evolutionary approach to solve the dynamic multihop ridematching problem

Multimedia Services in Cloud-Based Vehicular Networks

Lengvųjų automobilių stovėjimo aikštelių mieste vertinimas daugiatiksliais metodais

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