Advances in Swarm Intelligence 15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23–26, 2024, Proceedings, Part I

This two-volume set LNCS 14788 and 14789 constitutes the refereed post-conference proceedings of the 15th International Conference on Advances in Swarm Intelligence, ICSI 2024, held in Xining, China, during August 23–26, 2024.

The 74 revised full papers presented in these proceedings were carefully reviewed and selected from 156 submissions. The papers are organized in the following topical sections:

Part I - Particle swarm optimization; Swarm intelligence computing; Differential evolution; Evolutionary algorithms; Multi-agent reinforcement learning & Multi-objective optimization.

Part II - Route planning problem; Machine learning; Detection and prediction; Classification; Edge computing; Modeling and optimization & Analysis of review.

.- Particle Swarm Optimization.
.- Set-Based Particle Swarm Optimization for the Multi-Objective Multi-Dimensional Knapsack Problem.
.- Proposal of a Memory-Based Ensemble Particle Swarm Optimizer.
.- A Tri-swarm Particle Swarm Optimization Considering the Cooperation and the Fitness Value.
.- A Modified Variable Velocity Strategy Particle Swarm Optimization Algorithm for Multi-objective Feature Selection.
.- Multi-Strategy Enhanced Particle Swarm Optimization Algorithm for Elevator Group Scheduling.
.- A Self-Learning Particle Swarm Optimization Algorithm for Dynamic Job Shop Scheduling Problem with New Jobs Insertion.
.- Convolutional Neural Network Architecture Design Using An Improved Surrogate-assisted Particle Swarm Optimization Algorithm.
.- Swarm Intelligence Computing.
.- Cooperative Search and Rescue Target Assignment Based on Improved Ant Colony Algorithm.
.- A Metabolic Pathway Design Method based on surrogate-assisted Fireworks Algorithm.
.- Circle Chaotic Search-Based Butterfly Optimization Algorithm.
.- An Adaptive Bacterial Foraging Optimization Algorithm Based on Chaos-Enhanced Non-Elite Reverse Learning.
.- Enhanced Bacterial Foraging Optimization with Dynamic Disturbance Learning and Bilayer Nested Structure.
.- Improved Kepler Optimization Algorithm Based on Mixed Strategy.
.- Harmony Search with Dynamic Dimensional-reduction Adjustment Strategy for Large-scale Absolute Value Equation.
.- Massive Conscious Neighborhood-based Crow Search Algorithm for the Pseudo-Coloring Problem.
.- Multi-Strategy Integration Model Based on Black-Winged Kite Algorithm and Artificial Rabbit Optimization.
.- Differential Evolution.
.- Fractional Order Differential Evolution to Solve Parameter Estimation Problem of Solar Photovoltaic Models.
.- Enhanced Dingo Optimization Algorithm Based on Differential Evolution and Chaotic Mapping for Engineering Optimization.
.- Hierarchical Adaptive Differential Evolution with Local Search for Extreme Learning Machine.
.- Metaheuristic Algorithms for Enhancing Multicepstral Representation in Voice Spoofing Detection: An Experimental Approach.
.- Evolutionary Algorithms.
.- A Multi-modal Multi-objective Evolutionary Algorithm Based on Multi-criteria Grouping.
.- Constructing Robust and Influential Networks against Cascading Failures via a Multi-objective Evolutionary Algorithm.
.- Fault Reconfiguration of Distribution Networks Using an Enhanced Multimodal Multi-objective Evolutionary Algorithm.
.- Attacking Evolutionary Algorithms via SparseEA.
.- Evolutionary Computation with Distance-based Pretreatment for Multimodal Problems.
.- Multi-Agent Reinforcement Learning.
.- Stock Price Prediction Model Based on Blending Model Improved with Sentiment Factors and Double Q-learning.
.- Stock price prediction mdoel integrating an improved NSGA-III with Random Forest.
.- Unveiling the Decision-Making Process in Reinforcement Learning with Genetic Programming.
.- Diversity Improved Genetic Algorithm for Weapon Target Assignment.
.- An Investigation of Underground Rescue Scheduling with Multi-Agent Reinforcement Learning.
.- Distributed Advantage-based Weights Reshaping Algorithm with Sparse Reward.
.- Multi-objective Optimization.
.- A Joint Prediction Strategy based on Multiple Feature Points for Dynamic Multi-objective Optimization.
.- An Expensive Multi-objective Optimization Algorithm Based on Regional Density Ratio.
.- Robust Lightweight Neural Network Architecture Search-based on Multi-objective Particle Swarm Optimization.
.- Surrogate-Assisted Multi-Objective Evolutionary Algorithm Guided by Multi-Reference Points.
.- Multi-objective Path planning of Multiple Unmanned Air Vehicles Using the CCMO Algorithm.
.- Multi-UAV Collaborative Detection Based on Reinforcement Learning.