Search
Search Results
-
An Adaptive Knowledge Transfer Strategy for Evolutionary Dynamic Multi-objective Optimization
Dynamic multi-objective optimization problems (DMOPs) are optimization problems involve multiple conflicting objectives, and these objectives change...
-
A Non-uniform Clustering Based Evolutionary Algorithm for Solving Large-Scale Sparse Multi-objective Optimization Problems
Evolutionary algorithms have shown their effectiveness in solving sparse multi-objective optimization problems (SMOPs). However, for most of the...
-
A structure for predicting wind speed using fuzzy granulation and optimization techniques
With the increasing scarcity of global energy, the rapid development of science and technology, and the growing demand for environmental protection,...
-
MOAVOA: a new multi-objective artificial vultures optimization algorithm
This paper presents a multi-objective version of the artificial vultures optimization algorithm (AVOA) for a multi-objective optimization problem...
-
Multi-objective Optimization of Adhesive Bonding Process in Constrained and Noisy Settings
Finding the optimal process parameters for an adhesive bonding process is challenging: the optimization is inherently multi-objective (aiming to...
-
Use of a Surrogate Model for Symbolic Discretization of Temporal Data Sets Through eMODiTS and a Training Set with Varying-Sized Instances
Time series classification is a supervised task in the field of temporal data mining. Time series naturally tend to be highly dimensional, requiring...
-
Surrogate-assisted Multi-objective Optimization via Genetic Programming Based Symbolic Regression
Surrogate-assisted optimization algorithms are a commonly used technique to solve expensive-evaluation problems, in which a regression model is built...
-
Multi-guide particle swarm optimisation archive management strategies for dynamic optimisation problems
This study presents archive management approaches for dynamic multi-objective optimisation problems (DMOPs) using the multi-guide particle swarm...
-
Adaptive weighted kernel support vector machine-based circle search approach for intrusion detection in IoT environments
Nowadays, the Internet of Things (IoT) is considered a globally implemented technology in automated network structures. However, the procedures...
-
Experimental Validation of a Multi-objective Planning Decision Support System for Ship Routing Under Time Stress
Integration of sophisticated planning algorithms into Naval operations requires the systematic design of decision-support systems (DSS) that improve...
-
Load Models
This chapter deals with the models of IP packet streams generated by various applications. Initially, the characteristics of load models...
-
Multiobjective problem modeling of the capacitated vehicle routing problem with urgency in a pandemic period
This research is based on the capacitated vehicle routing problem with urgency where each vertex corresponds to a medical facility with a urgency...
-
Cross-Attention of Disentangled Modalities for 3D Human Mesh Recovery with Transformers
Transformer encoder architectures have recently achieved state-of-the-art results on monocular 3D human mesh reconstruction, but they require a...
-
Pareto Multi-task Deep Learning
Neuroevolution has been used to train Deep Neural Networks on reinforcement learning problems. A few attempts have been made to extend it to address...
-
A novel epsilon-dominance Harris Hawks optimizer for multi-objective optimization in engineering design problems
In this article, A Multi-Leaders Guided Harris Hawks optimizer using Epsilon-Dominance relation is developed for solving multi-objective optimization...
-
Multi-objective whale optimization algorithm and multi-objective grey wolf optimizer for solving next release problem with develo** fairness and uncertainty quality indicators
Selecting a set of requirements to implement in the next software release is an NP-Hard problem known as NRP. We propose multi-objective versions of...
-
Data transmission optimization in edge computing using multi-objective reinforcement learning
Reducing network energy consumption and balancing workload are two key optimization goals for data transmission in edge computing field. However,...
-
Efficient Causal Access in Geo-Replicated Storage Systems
We consider a setting where applications, such as websites or games, need causal access to objects available in geo-replicated cloud data stores....
-
A many-objective evolutionary algorithm based on novel fitness estimation and grou** layering
Many-objective optimization problems pose a great challenge for traditional Pareto-based multi-objective evolutionary algorithms (MOEAs), due to the...
-
Learning Heuristics for Multi-objective Dynamic Production Scheduling Problems
This chapter shows how genetic programming can learn a Pareto front of scheduling heuristics to cope with multiple conflicting objectives. A variety...