Lan, M. H. (2025) Multi-Objective Evolutionary Optimization for Qujing’s Cultural-Tourism Routes. Journal of Data Analysis ...
In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...
High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...
ABSTRACT: Visual Sensor Networks (VSNs) focus on capturing data, extracting relevant information, and enabling communication. However, the presence of obstacles affects network efficiency, linking ...
Abstract: Evolutionary Algorithms (EAs) are effective for solving Multi-Modal Multi-Objective Optimization Problems which optimal solutions subsets distributed regularly in the decision space.
In this study, we propose an exact method for optimizing a linear function over the efficient set of a multi-objective transportation problem (MOTP). This type of problem arises when a decision maker ...
Every engineer knows the pain of watching cloud bills spiral out of control. Businesses move workloads from on-premises data centers to public cloud providers, and the financial reality hits hard.
Multi-Factorial Evolutionary Algorithm With Online Transfer Parameter Estimation (MFEA-II) in Python
This repository implement MFEA-II MFEA-II Official Matlab Version. Tested on MTSOO benchmark. This repo could be used as a template or starter code for conducting multitasking optimization on other ...
Abstract: Solving constrained multi-objective optimization problems (CMOPs) is a challenging task due to the presence of multiple conflicting objectives and intricate constraints. In order to better ...
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