A survey of multiobjective evolutionary algorithms based on decomposition
Decomposition is a well-known strategy in traditional multiobjective optimization. However,
the decomposition strategy was not widely employed in evolutionary multiobjective …
the decomposition strategy was not widely employed in evolutionary multiobjective …
Decomposition-based hyperheuristic approaches for the bi-objective cold chain considering environmental effects
L Leng, J Zhang, C Zhang, Y Zhao, W Wang… - Computers & Operations …, 2020 - Elsevier
This paper proposed a novel approach for a practical version of the cold chain, namely
location-routing problem-based low-carbon cold chain (LRPLCCC). In the proposed bi …
location-routing problem-based low-carbon cold chain (LRPLCCC). In the proposed bi …
Comparative analysis of selection hyper-heuristics for real-world multi-objective optimization problems
As exact algorithms are unfeasible to solve real optimization problems, due to their
computational complexity, meta-heuristics are usually used to solve them. However …
computational complexity, meta-heuristics are usually used to solve them. However …
Decomposition multi-objective evolutionary optimization: From state-of-the-art to future opportunities
K Li - arXiv preprint arXiv:2108.09588, 2021 - arxiv.org
Decomposition has been the mainstream approach in the classic mathematical
programming for multi-objective optimization and multi-criterion decision-making. However …
programming for multi-objective optimization and multi-criterion decision-making. However …
A multi-objective hyper heuristic framework for integrated optimization of carrier-based aircraft flight deck operations scheduling and resource configuration
R Cui, W Han, X Su, Y Zhang, F Guo - Aerospace Science and Technology, 2020 - Elsevier
It is of great significance to produce an efficient flight deck operations scheduling plan for
improving the carrier-based aircraft sortie rate and enhancing the combat capability of …
improving the carrier-based aircraft sortie rate and enhancing the combat capability of …
A multiagent, dynamic rank-driven multi-deme architecture for real-valued multiobjective optimization
Multiobjective real parameter optimization is a challenging problem in majority of
engineering applications. This paper presents a creative multiagent and dynamic multi …
engineering applications. This paper presents a creative multiagent and dynamic multi …
A Survey of Decomposition-Based Evolutionary Multi-Objective Optimization: Part I-Past and Future
K Li - arXiv preprint arXiv:2404.14571, 2024 - arxiv.org
Decomposition has been the mainstream approach in classic mathematical programming for
multi-objective optimization and multi-criterion decision-making. However, it was not …
multi-objective optimization and multi-criterion decision-making. However, it was not …
Using multi-agent systems and social choice theory to design hyper-heuristics for multi-objective optimization problems.
VR Carvalho - 2022 - teses.usp.br
The majority of the most effective and efficient algorithms for multi-objective optimization are
based on Evolutionary Computation. However, choosing the most appropriate algorithm to …
based on Evolutionary Computation. However, choosing the most appropriate algorithm to …
Multiobjective great deluge algorithm with two-stage archive support
A multiobjective great deluge algorithm with a two-stage external memory support and
associated search operators exploiting the experience accumulated in memory are …
associated search operators exploiting the experience accumulated in memory are …
A multimetric and multideme multiagent system for multiobjective optimization
J Tamouk, A Acan - Computational Intelligence, 2018 - Wiley Online Library
This article proposes a multiagent system consisting of a number of multiobjective
metaheuristic agents (namely, multiobjective genetic algorithm, strength Pareto evolutionary …
metaheuristic agents (namely, multiobjective genetic algorithm, strength Pareto evolutionary …