Room 10A Schedule

First Day: June 6, 2017

09:45-10:45: Evolutionary Computing Applications in Hardware

• A Dynamic Search Space Approach to Improving Learning in a Simulated Flapping Wing Micro Air Vehicle
• Multi-objective Evolution of Hash Functions for High Speed Networks
• Towards the development of a complete GP system on an FPGA using geometric semantic operators

11:15-13:15: Evolutionary Methods and Machine Learning: Data Preprocessing, Learning Models and Their Applications I

• Multi-view semi-supervised learning using Genetic Programming interpretable classification rules
• Learning Heuristic Selection using a Time Delay Neural Network for Open Vehicle Routing
• Generation of first-order TSK rules based on the apriori + search
• An evolutionary algorithm for mining rare association rules: a Big Data approach
• An Evolutionary Algorithm for Optimizing the Target Ordering in Ensemble of Regressor Chains
• Estimation of Distribution Algorithms for Decision-Tree Induction

14:30-16:30: Evolutionary Methods and Machine Learning in SE, Testing and SE Repositories

• A Multi-objective and Cost-Aware Optimization of Requirements Assignment
• Using Evolutionary Mutation Testing to Improve the Quality of Test Suites
• Search-Based Test Case Generation for Cyber-Physical Systems
• Search-Based Requirements Traceability Recovery: A Multi-Objective Approach
• On the Effect of Local Search in the Multi-objective Evolutionary Discovery of Software Architectures
• The Consolidated Tree Construction Algorithm in Imbalanced Defect Prediction Datasets

Second Day: June 7, 2017

09:45-10:45: Diversity Preservation Mechanisms for Population-Based Metaheuristics

• Diversity-Based Adaptive Genetic Algorithm for a Workforce Scheduling and Routing Problem
• The Importance of the Individual Encoding in Memetic Algorithms with Diversity Control Applied to Large Sudoku Puzzles
• A Memetic Algorithm for the Capacitated Vehicle Routing Problem with Time Windows

11:15-13:15: Discrete and Combinatorial Optimization I

• An Adaptive Large Neighborhood Search with Learning Automata for the Unrelated Parallel Machine Scheduling Problem
• On Asymptotic Complexity of the Optimum Golomb Ruler Problem: From Established Stochastic Methods to Self-Avoiding Walks
• Applying the Biased Form of the Adaptive Generative Representation
• A Square Lattice Probability Model for Optimising the Graph Partitioning Problem
• Improving local search in a minimum vertex cover solver for classes of networks
• On the Evolution of Bent (n, m) Functions

14:30-16:30: Classification, Clustering, Data Analysis and Data Mining I

• Many-objective optimization for Community Detection in multi-layer networks
• An Improved Multiobjective Evolutionary Approach for Community Detection in Multilayer Networks
• Finding Multi-Density Clusters in Non-Stationary Data Streams Using an Ant Colony with Adaptive Parameters
• Vector Representation of Non-standard Spellings Using Dynamic Time Wrapping and a Denoising Autoencoder
• Unsupervised Method to Ensemble Results of Multiple Clustering Solutions for Bibliographic Data
• Probabilistic Graphs to Model Pseudomonas aeruginosa Survival Mechanism and Infer Low Nutrient Water Response Genes

Third Day: June 8, 2017

09:45-10:45: Fitness Landscape Analysis for Understanding and Designing Intelligent Optimization Algorithms

• Characterising Neutrality in Neural Network Error Landscapes
• Local Optima Networks of the Permutation Flowshop Scheduling Problem: Makespan vs. Total Flow Time
• Bandit-Based Random Mutation Hill-Climbing

11:15-13:15: Particle Swarm Optimization

• The Effect of Evaluation Time Variance on Asynchronous Particle Swarm Optimization
• Optimal Parameter Regions for Particle Swarm Optimization Algorithms
• Vector Evaluated Particle Swarm Optimization: The Archive's Influence on Performance
• Convergence Criteria for the Particle Swarm Optimization in a Full Iterative Process
• PSO-based Search Mechanism in Dynamic Environments: Swarms in Vector Fields
• Multiple-Particle Swarm Optimization used to study material degradation in aeroelastic composites including probabalistic uncertainties