@Article{Gunpinar2019,
author="Gunpinar, Erkan
and Khan, Shahroz",
title="A multi-criteria based selection method using non-dominated sorting for genetic algorithm based design",
journal="Optimization and Engineering",
year="2019",
month="Nov",
day="29",
abstract="The paper presents a generative design approach, particularly for simulation-driven designs, using a genetic algorithm (GA), which is structured based on a novel offspring selection strategy.The proposed selection approach commences while enumerating the offsprings generated from the selected parents. Afterwards, a set of eminent offsprings is selected from the enumerated ones based on the following merit criteria: space-fillingness to generate as many distinct offsprings as possible, resemblance/non-resemblance of offsprings to the good/bad individuals, non-collapsingness to produce diverse simulation results and constrain-handling for the selection of offsprings satisfying design constraints. The selection problem itself is formulated as a multi-objective optimization problem. A greedy technique is employed based on non-dominated sorting, pruning, and selecting the representative solution. According to the experiments performed using three different application scenarios, namely simulation-driven product design, mechanical design and user-centred product design, the proposed selection technique outperforms the baseline GA selection techniques, such as tournament and ranking selections.",
issn="1573-2924",
doi="10.1007/s11081-019-09477-8",
url="https://doi.org/10.1007/s11081-019-09477-8"
}