TWO-STEP META-HEURISTIC APPROACH FOR A VEHICLE ASSIGNMENT PROBLEM - CASE FROM ISTANBUL/TURKEY
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Date
2020
Authors
Journal Title
Journal ISSN
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Publisher
Svenciliste U Zagrebu, Fakultet Prometnih Znanosti
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
In this paper, a two-step meta-heuristic approach is proposed for vehicle assignment problem with geometric shape-based clustering and genetic algorithm. First, the geometric shape-based clustering method is used and then the solution of this method is given to the genetic algorithm as initial solution. The solution process is continued by genetic algorithm. There are 282 bus lines in Istanbul European side. Those buses should be assigned to six bus garages. The proposed method is used to determine the minimum distance between the bus lines and garages by assigning buses to garages. According to the computational results, the proposed algorithm has better clustering performance in terms of the distance from each bus-line start point to each bus garage in the cluster. The crossover rate changing method is also applied as a trial in order to improve the algorithm performance. Finally, the outputs that are generated by different crossover rates are compared with the results of the k-Nearest Neighbour algorithm to prove the effectiveness of the study.
Description
Keywords
vehicle assignment problem, geometric shape-based clustering, genetic algorithm, crossover rate, the k-Nearest Neighbour algorithm
Journal or Series
Promet-Traffic & Transportation
WoS Q Value
Q4
Scopus Q Value
Volume
32
Issue
1
