Development of soft computing Models for vehicle routing problem

dc.contributor.guideSivakumar, R and Rajkumar, N
dc.coverage.spatialDevelopment of soft computing Models for vehicle routing problem
dc.creator.researcherSundar ganesh, C S
dc.date.accessioned2023-01-30T09:48:49Z
dc.date.available2023-01-30T09:48:49Z
dc.date.awarded2021
dc.date.completed2021
dc.date.registered
dc.description.abstractVehicle Routing Problem is formulated to tackle the delivery problem while distributing fuel to delivery stations. The vehicle routing problems, which incorporates, capacitated vehicle routing problem, vehicle routing problem with time windows, and the time elapsed to serve each customer.The capacitated vehicle routing problem wherein it is required to route suitable vehicles with limited capacity in the highway to meet the client requests to minimize the operational cost. In certain cases, the client shall specify a period-window with an early and final time for the delivery and this comes under the class of vehicle routing problem with time windows. newlineThe major intentions of this research work are to formulate a novel fuzzy time series model, modified multi-verse and unified multi-verse optimizer, hybrid multi-verse grasshopper optimization for solving vehicle routing issues. The vehicle routing issue taken for the research is the dynamic VRPTW with Solomon s data sets. The target is to find the minimum number of vehicles and distance travelled and conducts a comparative analysis with respect to the number of vehicles, distance travelled, and computational time for all the developed techniques and to validate the proposed models. newlineA multi-target dynamic vehicle directing issue with fuzzy time arrangement has been discussed and analyzed. This model provides better solutions in the class of Solomon s R1 and R2 data instances for minimization of distance travelled. The proposed MMVO techniques are applied over R, C, and RC instances. For Solomon instance RC206, MMVO attained a minimized distance of 1047.25 with 3 vehicles better than the other methods. newline
dc.description.note
dc.format.accompanyingmaterialNone
dc.format.dimensions21cm
dc.format.extentxvii,157p.
dc.identifier.urihttp://hdl.handle.net/10603/454789
dc.languageEnglish
dc.publisher.institutionFaculty of Technology
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.relationp.144-156
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering
dc.subject.keywordMechanics
dc.subject.keywordDynamic Vehicle Routing Problem
dc.subject.keywordMulti Verse Optimization
dc.subject.keywordGrass Hopper optimization
dc.titleDevelopment of soft computing Models for vehicle routing problem
dc.title.alternative
dc.type.degreePh.D.

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