407 citations · 440 across the 10 of their papers we have counts for
Showing 2020 · cs.AIShow all
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cs.AI2020
On the Transferability of Knowledge among Vehicle Routing Problems by using Cellular Evolutionary Multitasking
Eneko Osaba, Aritz D. Martinez, Jesus L. Lobo +2
Multitasking optimization is a recently introduced paradigm, focused on the simultaneous solving of multiple optimization problem instances (tasks). The goal of multitasking enviro…
cs.AI2020★ 23 cited
dMFEA-II: An Adaptive Multifactorial Evolutionary Algorithm for Permutation-based Discrete Optimization Problems
Eneko Osaba, Aritz D. Martinez, Akemi Galvez +2
The emerging research paradigm coined as multitasking optimization aims to solve multiple optimization tasks concurrently by means of a single search process. For this purpose, the…