Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Continuous dynamic optimisation using evolutionary algorithms
Experimental study on population-based incremental learning algorithms for dynamic optimization problems
A Tutorial on Evolutionary Multiobjective Optimization
A Vector Angle-Based Evolutionary Algorithm for Unconstrained Many-Objective Optimization
Solving portfolio optimization problem through differential evolution
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
An Evolution Strategy with Momentum Adaptation of the Random Number Distribution.
An Introduction to Simulated Evolutionary Optimization
Genetic Algorithms and Engineering Optimization
Evolutionary Algorithms for Reinforcement Learning
differential evolution - a simple and efficient heuristic for global optimization over continuous spaces .
Objective Reduction in Evolutionary Multiobjective Optimization: Theory and Applications
A Comprehensive Survey of Evolutionary-Based Multiobjective Optimization Techniques
The CMA Evolution Strategy: A Tutorial
A Comparison of Global Search Algorithms for Continuous Black Box Optimization
Multi-Objective Optimization Using Genetic Algorithms: A Tutorial
Preference-guided evolutionary algorithms for many-objective optimization
A survey of swarm intelligence for dynamic optimization: Algorithms and applications
An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition
DEAP: a python framework for evolutionary algorithms
Evolutionary Programming in Electromagnetic Optimization: A Review
Learning unified features from natural and programming languages for locating buggy source code
Structured Wiki with Annotation for Knowledge Management: an Application to Cultural Heritage
Pathological pain and the neuroimmune interface
MULTITEMPORAL HYPERSPECTRAL DATA ANALYSIS FOR REGIONAL DETECTION OF PLANT STRESS BY USING AN AIRBORNE- AND TRACTOR-BASED SPECTROMETER – CASE STUDY: SUGAR BEET DISEASE RHIZOCTONIA SOLANI –
nonstationary function optimization using genetic algorithms with dominance and diploidy .