New heuristic algorithms for discrete competitive location problems with binary and partially binary customer behavior P Fernández, B Pelegrín, A Lančinskas, J Žilinskas Computers & Operations Research 79, 12-18, 2017 | 54 | 2017 |

A preference-based multi-objective evolutionary algorithm R-NSGA-II with stochastic local search E Filatovas, A Lančinskas, O Kurasova, J Žilinskas Central European Journal of Operations Research 25, 859-878, 2017 | 32 | 2017 |

Pooled testing with replication as a mass testing strategy for the COVID-19 pandemics J Žilinskas, A Lančinskas, MR Guarracino Scientific Reports 11 (1), 3459, 2021 | 29 | 2021 |

Improving solution of discrete competitive facility location problems A Lančinskas, P Fernández, B Pelegín, J Žilinskas Optimization Letters 11, 259-270, 2017 | 28 | 2017 |

Effect of diffusion limitations on multianalyte determination from biased biosensor response R Baronas, J Kulys, A Lančinskas, A Žilinskas Sensors 14 (3), 4634-4656, 2014 | 28 | 2014 |

Solution of multi-objective competitive facility location problems using parallel NSGA-II on large scale computing systems A Lančinskas, J Żilinskas Applied Parallel and Scientific Computing: 11th International Conference …, 2013 | 20 | 2013 |

Multi-objective single agent stochastic search in non-dominated sorting genetic algorithm A Lančinskas, PMM Ortigosa, J Žilinskas Nonlinear Analysis: Modelling and Control 18 (3), 293-313, 2013 | 18 | 2013 |

Exact and heuristic solutions of a discrete competitive location model with Pareto-Huff customer choice rule P Fernández, B Pelegrín, A Lančinskas, J Žilinskas Journal of Computational and Applied Mathematics 385, 113200, 2021 | 17 | 2021 |

Optimization of the multianalyte determination with biased biosensor response R Baronas, J Kulys, A Žilinskas, A Lančinskas, D Baronas Chemometrics and Intelligent Laboratory Systems 126, 108-116, 2013 | 12 | 2013 |

Approaches to parallelize pareto ranking in NSGA-II algorithm A Lančinskas, J Žilinskas Parallel Processing and Applied Mathematics: 9th International Conference …, 2012 | 12 | 2012 |

Solution of asymmetric discrete competitive facility location problems using ranking of candidate locations A Lančinskas, J Žilinskas, P Fernández, B Pelegrín Soft Computing 24, 17705-17713, 2020 | 11 | 2020 |

Parallel optimization algorithm for competitive facility location A Lančinskas, PM Ortigosa, J Žilinskas Mathematical Modelling and Analysis 20 (5), 619-640, 2015 | 11 | 2015 |

A discrete competitive facility location model with minimal market share constraints and equity-based ties breaking rule P Fernández, A Lančinskas, B Pelegrín, J Žilinskas Informatica 31 (2), 205-224, 2020 | 10 | 2020 |

On benchmarking stochastic global optimization algorithms EMT Hendrix, A Lančinskas Informatica 26 (4), 649-662, 2015 | 10 | 2015 |

Solution of discrete competitive facility location problem for firm expansion A Lančinskas, P Fernandez, B Pelegrin, J Žilinskas Informatica 27 (2), 451-462, 2016 | 7 | 2016 |

Application of multi-objective optimization to pooled experiments of next generation sequencing for detection of rare mutations J Žilinskas, A Lančinskas, MR Guarracino PLoS One 9 (9), e104992, 2014 | 6 | 2014 |

Parallel multi-objective memetic algorithm for competitive facility location A Lančinskas, J Žilinskas Parallel Processing and Applied Mathematics: 10th International Conference …, 2014 | 5 | 2014 |

Atsitiktinės paieškos globaliojo optimizavimo algoritmų lygiagretinimas A Lančinskas | 5 | 2013 |

Investigation of parallel particle swarm optimization algorithm with reduction of the search area A Lančinskas, J Žilinskas, PM Ortigosa 2010 IEEE International Conference On Cluster Computing Workshops and …, 2010 | 5 | 2010 |

The huff versus the pareto-huff customer choice rules in a discrete competitive location model P Fernández, B Pelegrín, A Lančinskas, J Žilinskas Computational Science and Its Applications–ICCSA 2018: 18th International …, 2018 | 4 | 2018 |