@inproceedings{scholars14687,
           pages = {213--219},
         journal = {Proceedings - International Conference on Computer and Information Sciences: Sustaining Tomorrow with Digital Innovation, ICCOINS 2021},
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
           title = {Multi-Population Genetic Algorithm for Rich Vehicle Routing Problems},
            year = {2021},
             doi = {10.1109/ICCOINS49721.2021.9497136},
            note = {cited By 0; Conference of 6th International Conference on Computer and Information Sciences, ICCOINS 2021 ; Conference Date: 13 July 2021 Through 15 July 2021; Conference Code:170762},
        abstract = {Genetic algorithm (GA) is a metaheuristic method that has been widely adopted for solving the Rich Vehicle Routing Problems (RVRP) due to its ability to find quality approximate solutions, even for large-scale instances of the problem, in a reasonable time. However, GA is stochastic in nature and does not guarantee a good solution all the time, a problem primarily due to premature convergence. In this paper we present Multi-population Genetic Algorithm for Rich Vehicle Routing Problems (MPGA-RVRP) to provide diversity and delay premature convergence in GA by making use of multiple populations that each evolves independently optimizing a single objective while sharing potential solutions. MPGA-RVRP is applied in RVRP with three objectives:- total route distance, total route duration and total route cost. Results from the experiments show that MPGA-RVRP performs considerably better compared to benchmark, multi-objective Genetic Algorithm (MOGA). {\^A}{\copyright} 2021 IEEE.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112464766&doi=10.1109\%2fICCOINS49721.2021.9497136&partnerID=40&md5=54bef794176e6bb186b8db8dd38c147d},
        keywords = {Routing algorithms; Stochastic systems; Vehicle routing; Vehicles, Approximate solution; Meta-heuristic methods; Multi-objective genetic algorithm; Multi-population genetic algorithm; Multiple populations; Pre-mature convergences; Single objective; Vehicle Routing Problems, Genetic algorithms},
            isbn = {9781728171517},
          author = {Agany Manyiel, J. M. and Kwang Hooi, Y. and Zakaria, M. N. B.}
}