Sep 5, 2017 · In this paper, we proposed a new steady-state MOEA/D with the preference to search the region of Pareto front near the true sparse solution.

In this paper, we proposed a new steady-state MOEA/D with the preference to search the region of Pareto front near the true sparse solution. Within each ...

The major advantages of MOEA/D lie in two aspects: (1) free setting of regularization parameter and (2) detection of true sparsity. Due to the generational mode ...

Sep 6, 2017 · In this paper, we proposed a new steady-state MOEA/D with the preference to search the region of Pareto front near the true sparse solution.

Authors: Hui Li, Jianyong Sun, Yuanyuan Fan, Mingyang Wang, Qingfu Zhang.

Abstract: The classical algorithms based on regularization usually solve sparse optimization problems under the framework of single objective optimization, ...

In this paper, we proposed a revised version of MOEA/D based on iterative thresholding algorithm for sparse optimization. It only aims at finding a local part ...

Sep 29, 2021 · We propose a MOEA/D with adaptive exploration and exploitation, termed MOEA/D-AEE, which adopts random numbers with a uniform distribution to explore the ...

We compare SSWA with eight state-of-the-art weight adaptative decomposition-based MOEAs and show its general outperformance on problems with various Pareto ...

A revised version of MOEA/D based on iterative thresholding algorithm for sparse optimization that only aims at finding a local part of trade-off solutions, ...