Search Results - "Multifactorial evolutionary algorithm"

AT-MFCGA: An Adaptive Transfer-guided Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking by Osaba, Eneko, Del Ser, Javier, Martinez, Aritz D., Lobo, Jesus L., Herrera, Francisco

“…•An adaptive and transfer guided metaheuristic is proposed for Evolutionary Multitasking.•Synergies between tasks are analyzed along the search in a dynamic…”
Get full text

Toward Adaptive Knowledge Transfer in Multifactorial Evolutionary Computation by Zhou, Lei, Feng, Liang, Tan, Kay Chen, Zhong, Jinghui, Zhu, Zexuan, Liu, Kai, Chen, Chao

“…A multifactorial evolutionary algorithm (MFEA) is a recently proposed algorithm for evolutionary multitasking, which optimizes multiple optimization tasks…”
Get full text

Evolutionary algorithm and multifactorial evolutionary algorithm on clustered shortest-path tree problem by Hanh, Phan Thi Hong, Thanh, Pham Dinh, Binh, Huynh Thi Thanh

“…In literature, Clustered Shortest-Path Tree Problem (CluSPT) is an NP-hard problem. Previous studies focus on approximation algorithms which search for an…”
Get full text

Individualized requirement-driven multi-task scheduling in cloud manufacturing using an extended multifactorial evolutionary algorithm by Zhang, Wenyu, Xiao, Jiuhong, Liu, Weishu, Sui, Yongfeng, Li, Yongfeng, Zhang, Shuai

“…•A new individualized requirement-driven cloud manufacturing multi-task scheduling model is proposed.•The proposed model aims to maximize the benefits not only…”
Get full text

A surrogate assisted evolutionary multitasking optimization algorithm by Yang, Shangqi, Qi, Yutao, Yang, Rui, Ma, Xiaoliang, Zhang, Haibin

“…Evolutionary algorithms (EAs) have been applied with strong abilities to solve a wide range of applications, but it can solve one problem at a time. To improve…”
Get full text

Meta-Learning Inspired Single-Step Generative Model for Expensive Multitask Optimization Problems by Wang, Ruilin, Feng, Xiang, Yu, Huiqun, Tan, Yang, Lai, Edmund M-K

“…In expensive multitask optimization problems (ExMTOPs), multiple complex tasks must be optimized simultaneously under limited computational budgets. Existing…”
Get full text

An online transfer learning based multifactorial evolutionary algorithm for solving the clustered Steiner tree problem by Long, Nguyen Binh, Anh, Do Tuan, Ban, Ha-Bang, Binh, Huynh Thi Thanh

“…The rapid increase in the number and computing power of devices interacting through the network over the past few years has led to a growing trend of…”
Get full text

Adaptive Knowledge Transfer in Multifactorial Evolutionary Algorithm for the Clustered Minimum Routing Cost Problem by Thang, Ta Bao, Long, Nguyen Binh, Hoang, Ngo Viet, Binh, Huynh Thi Thanh

“…Having tremendous promising impact on society, the Internet of Things refers to the connection of millions of worldwide devices to communicate and exchange…”
Get full text

Multi-objective evolutionary multi-tasking algorithmusing cross-dimensional and prediction-based knowledge transfer by Chen, Qunjian, Ma, Xiaoliang, Yu, Yanan, Sun, Yiwen, Zhu, Zexuan

“…•A novel evolutionary multiobjective multi-tasking algorithm MS-MOMFEA is proposed.•Cross-dimensional search is introduced to accelerate the…”
Get full text

Contrastive variational auto-encoder driven convergence guidance in evolutionary multitasking by Wang, Ruilin, Feng, Xiang, Yu, Huiqun

“…Knowledge transfer is at the core of the Evolutionary Multitasking (EMT) problem, as it exploits the interaction of inter-task common knowledge to accelerate…”
Get full text

Multi-objective evolutionary multi-tasking algorithm using cross-dimensional and prediction-based knowledge transfer by Chen, Qunjian, Ma, Xiaoliang, Yu, Yanan, Sun, Yiwen, Zhu, Zexuan

Get full text

Towards urban energy sustainability and resiliency through smart agriculture and effective renewable resource allocation by Cheng, Lijun, Samah, Azurah, Zhang, Yubo, Jia, Zongwei, Li, Fuzhong

“…Urban energy sustainability and resiliency are paramount in addressing the challenges of modern urbanization. This paper introduces a novel framework that…”
Get full text

Enhancing evolutionary multitask optimization by multidimensional scaling and golden section search by Luo, Guoxing, Fan, Jihua, Li, Yanhui, Ma, Xiaoliang

“…•An MDS-based LDA method aligns latent subspaces for knowledge transfer.•A GSS-based strategy avoids local optima and enhances population diversity.•The…”
Get full text

An improved multi-objective multifactorial evolutionary algorithm for assembly line balancing problem considering regular production and preventive maintenance scenarios by Tang, Qiuhua, Meng, Kai, Cheng, Lixin, Zhang, Zikai

“…•ALBP considering PM scenarios promotes the productivity and smoothness.•Multi-task optimization benefits the simultaneous optimization of all scenarios.•The…”
Get full text

A comparison of different clustering algorithms for the project time buffering problem by Cao, Fangfang, Servranckx, Tom, Vanhoucke, Mario, He, Zhengwen

“…This paper studies the decentralised time buffering problem (TBP) to absorb project risk by building sufficient buffers with the aim of obtaining a stable…”
Get full text

Multitask Augmented Random Search in deep reinforcement learning by Thanh, Le Tien, Thang, Ta Bao, Cuong, Le Van, Binh, Huynh Thi Thanh

“…Reinforcement Learning (RL) has gained significant popularity in recent years for its ability to solve complex control problems. However, most existing RL…”
Get full text

Enhancing evolutionary multitasking optimization by leveraging inter-task knowledge transfers and improved evolutionary operators by Ma, Xiaoliang, Xu, Mingyu, Yu, Yanan, Liu, Hongjie, Wang, Yan, Wang, Lei, Qi, Yutao, Xiong, Jian

“…It is inefficient and time-consuming to begin the search from scratch for each optimization task. Evolutionary multitasking optimization (EMTO) handles…”
Get full text

Multifactorial Evolutionary Algorithm Based on Diffusion Gradient Descent by Liu, Zhaobo, Li, Guo, Zhang, Haili, Liang, Zhengping, Zhu, Zexuan

“…The multifactorial evolutionary algorithm (MFEA) is one of the most widely used evolutionary multitasking (EMT) algorithms. The MFEA implements knowledge…”
Get full text

Multifactorial Genetic Programming for Symbolic Regression Problems by Zhong, Jinghui, Feng, Liang, Cai, Wentong, Ong, Yew-Soon

“…Genetic programming (GP) is a powerful evolutionary algorithm that has been widely used for solving many real-world optimization problems. However, traditional…”
Get full text

Evolutionary Multitask Optimization: a Methodological Overview, Challenges, and Future Research Directions by Osaba, Eneko, Del Ser, Javier, Martinez, Aritz D., Hussain, Amir

“…In this work, we consider multitasking in the context of solving multiple optimization problems simultaneously by conducting a single search process. The…”
Get full text