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<p>Modelling an Efficient Hybrid Optimizer for Handling Vehicle Routing Problem</p>

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Title Statement <p>Modelling an Efficient Hybrid Optimizer for Handling Vehicle Routing Problem</p>
 
Added Entry - Uncontrolled Name Velusamy, Praveen ; Bannari Amman Institute of Technology, Sathyamangalam 638 401, Tamilnadu, India
Keerthika, P ; Kongu Engineering College, Perundurai 638 052, Tamilnadu, India
 
Uncontrolled Index Term Grey wolf optimization, Linear measure, Multi-constraint problem, Particle swarm optimization, Routing distance
 
Summary, etc. <p class="Abstract">Vehicle Routing Problem (VRP) like total routing distance, number of serve provisioning vehicles, and vehicles' waiting time are determined as the multi-objective constraints. Investigators pretend to handle these multi-constraint issues with the time window and fail to attain a prominent solution. Thus, there is a need for a global multi-objective vehicle routing solution. Here, a novel Particle Positioning Particle Swarm Optimization ( ) approach is designed to predict the robust route with the elimination of non-linearity measures. The linearity measure includes the movement of the vehicles, service time, and status of the move towards a particular direction. The lack of exploration and exploitation conditions during optimization is addressed with the inclusion of Grey Wolf Optimization (GWO). Therefore, the models attain a global solution with the least error rate. Simulation is done in MATLAB 2016b environment, and the experimental outcomes are compared with various approaches in large-scale and small-scale instances. The model intends to attain robustness and stability towards the measure in a linear manner. The model's time consumption and computational complexity are reduced with the adoption of a global routing-based optimization approach.</p>
 
Publication, Distribution, Etc. Journal of Scientific and Industrial Research (JSIR)
2022-07-25 10:12:01
 
Electronic Location and Access application/pdf
http://op.niscair.res.in/index.php/JSIR/article/view/61849
 
Data Source Entry Journal of Scientific and Industrial Research (JSIR); ##issue.vol## 81, ##issue.no## 06 (2022): Journal of Scientific and Industrial Research
 
Language Note en