Advances in Swarm Intelligence: 12th International Conference, ICSI 2021, Qingdao, China, July 17–21, 2021, Proceedings, Part I (Lecture Notes in Computer Science, 12689)

Preface
Organization
Contents – Part I
Contents – Part II
Swarm Intelligence and Nature-Inspired Computing
Swarm Unit Digital Control System Simulation
	1 Introduction
	2 Features of Von Neumann Computer Control
	3 Semi-Markov Model of DC Operation
	4 Example of Control System Analysis
	5 Conclusion
	References
Natural Emergence of Heterogeneous Strategies in Artificially Intelligent Competitive Teams
	1 Introduction
	2 Related Work
		2.1 Multi-agent Reinforcement Learning
		2.2 Multi-agent Environments
	3 Method
		3.1 Modeling Observation of Opponents
		3.2 Modeling Interactions with Teammates
		3.3 Policy
		3.4 Scalability and Real World Applicability
		3.5 Training
	4 Environment
		4.1 Observation Space
		4.2 Action Space
		4.3 Reward Structure
	5 Results
		5.1 Evolution of Strategies
		5.2 Being Attentive
		5.3 Ensemble Strategies
	6 Conclusions
	References
Analysis of Security Problems in Groups of Intelligent Sensors
	1 Introduction
	2 Analysis of Information Security Problems of the Internet of Things as a Group with Swarm Intelligence
	3 Exploitation Vulnerabilities
	4 Internet of Things and Lightweight Cryptography
	5 The Tiny Encryption Algorithm Cipher Description
	6 Speck Cipher Description
	7 Experimental Research of Encryption Algorithms
	8 Conclusion
	References
Optimization of a High-Lift Mechanism Motion Generation Synthesis Using MHS
	1 Introduction
	2 High-Lift Mechanism
	3 Optimization Problem and Constraint Handling
	4 The Design Results
	5 Conclusion and Discussion
	References
Liminal Tones: Swarm Aesthetics and Materiality in Sound Art
	1 Introduction
	2 Methods
		2.1 Concept
		2.2 Model
	3 Results
	4 Discussion and Future Works
		4.1 Order and Chaos – Sound as Emergence
		4.2 Future Works
	References
Study on the Random Factor of Firefly Algorithm
	1 Introduction
	2 Review of FA
		2.1 Algorithm Idea
		2.2 Model Analysis of FA
	3 Research on the Random Factor Control Method of FA
		3.1 Problem Analysis
		3.2 New Control Method for the Random Factor
	4 Experimental Results
		4.1 Experiment Design
		4.2 Results Analysis
		4.3 Comparison with Other Decreasing Control Methods
		4.4 Performance Comparison with Other Swarm Intelligence Algorithms
	5 Conclusion
	References
Metaheuristic Optimization on Tensor-Type Solution via Swarm Intelligence and Its Application in the Profit Optimization in Designing Selling Scheme
	1 Introduction
	2 A Brief Review of PSO and SIB
	3 Method and Implementation
	4 Applications
	5 Conclusion
	References
An Improved Dragonfly Algorithm Based on Angle Modulation Mechanism for Solving 0–1 Knapsack Problems
	1 Introduction
	2 Dragonfly Algorithm
	3 Improved Angle Modulated Dragonfly Algorithm (IAMDA)
		3.1 AMDA
		3.2 IAMDA
	4 Experimental Results and Discussion
	5 Conclusions
	References
A Novel Physarum-Based Optimization Algorithm for Shortest Path
	1 Introduction
	2 Classical Physarum Algorithm
		2.1 Basic Notations
		2.2 Physarum Algorithm
	3 Novel Physarum-Based Algorithm
		3.1 Method 1: Quickly Removing Redundant Edges
		3.2 Method 2: Merging Redundant Nodes
	4 Computational Experiments
	5 Conclusions
	References
Traveling Salesman Problem via Swarm Intelligence
	1 Introduction
	2 The Swarm Intelligence Based Method for Solving TSP
		2.1 Initialization Step
		2.2 Iteration Step
	3 Performance of SIB for TSP
		3.1 Implementations
		3.2 Results
		3.3 Discussion
	4 Conclusion
	References
Swarm-Based Computing Algorithms for Optimization
Lion Swarm Optimization by Reinforcement Pattern Search
	1 Introduction
	2 Modified Lion Swarm Optimization
		2.1 Lion Swarm Optimization
		2.2 Problems with LSO
		2.3 Modifications to LSO
	3 Reinforcement Pattern Search
		3.1 Pattern Search
		3.2 Q-learning
		3.3 Reinforcement Pattern Search Algorithm
	4 Lion Swarm Optimization by Reinforcement Pattern Search
	5 Experiment and Analysis
		5.1 Experimental Setup
		5.2 Comparison of Experimental Results
	6 Conclusion
	References
Fuzzy Clustering Algorithm Based on Improved Lion Swarm Optimization Algorithm
	1 Introduction
	2 The Basic Theory
		2.1 Fuzzy C-Mean Clustering
		2.2 Lion Swarm Optimization Algorithm
		2.3 Sin Cos Algorithm
		2.4 Elite Opposition-Based Learning
	3 The Improved Lion Swarm Optimization Algorithm
		3.1 The Improved Lion Swarm Optimization Algorithm
		3.2 Algorithm Process
		3.3 Performance Comparison and Analysis
	4 Experimental Results and Analysis
		4.1 FCM Algorithm Based on ILSO Algorithm
		4.2 Database
		4.3 Experimental Results and Analysis
	5 Conclusion
	References
Sparrow Search Algorithm for Solving Flexible Jobshop Scheduling Problem
	1 Introduction
	2 Problem Formulation
		2.1 T-FJSP and P-FJSP
		2.2 The Relationship Between JSP and FJSP
		2.3 Symbol Definition and Description
		2.4 The Mathematical Model of FJSP
	3 Sparrow Search Algorithm
		3.1 Biological Basis
		3.2 Algorithm Description of SSA
	4 Validation and Comparison
	5 Conclusion
	References
Performance Analysis of Evolutionary Computation Based on Tianchi Service Scheduling Problem
	1 Introduction
	2 Tianchi Service Scheduling Problem
	3 Proposed Solution
	4 Experimental Evaluation
	5 Discussions
	6 Conclusion
	References
An Intelligent Algorithm for AGV Scheduling in Intelligent Warehouses
	1 Introduction
	2 Related Work
	3 Problem Description
	4 A Hybrid Intelligent Algorithm for the Problem
		4.1 Tabu Search for AGV Routing
		4.2 WWO for Allocating Tasks to AGVs
	5 Computational Experiments
	6 Conclusion
	References
Success-History Based Position Adaptation in Gaining-Sharing Knowledge Based Algorithm
	1 Introduction
	2 Gaining-Sharing Knowledge Based Algorithm
	3 Proposed Adaptation
	4 Experimental Results
		4.1 Benchmark Functions and Experimental Setup
		4.2 Numerical Results
	5 Conclusions
	References
Particle Swarm Optimization
Multi-guide Particle Swarm Optimisation Control Parameter Importance in High Dimensional Spaces
	1 Introduction
	2 Background
		2.1 Multi-objective Optimization
		2.2 Multi-guide Particle Swarm Optimization
		2.3 Functional Analysis of Variance
	3 Experimental Procedure
	4 Results
		4.1 Control Parameter Importance for Higher Dimensional Problems
		4.2 Control Parameter Importance over Time
	5 Conclusions
	References
Research on the Latest Development of Particle Swarm Optimization Algorithm for Satellite Constellation
	1 Introduction
	2 Particle Swarm Optimization (PSO)
	3 Binary Particle Swarm Optimization (BPSO)
	4 Modified Binary Particle Swarm Optimization (MBPSO)
	5 Hybrid-Resampling Particle Swarm Optimization (HRPSO)
	6 Conclusions and Future Work
	References
Polynomial Approximation Using Set-Based Particle Swarm Optimization
	1 Introduction
	2 Background
		2.1 Polynomial Regression
		2.2 Particle Swarm Optimization
		2.3 Adaptive Coordinate Descent
	3 Set-Based Particle Swarm Optimization Polynomial Regression
	4 Empirical Process
		4.1 Benchmark Problems
		4.2 Tuning Algorithm Configurations
		4.3 Performance Measures
	5 Results
		5.1 SBPSO and BPSO Results
		5.2 Hybrid and PSO Results
	6 Conclusions and Future Work
	References
Optimizing Artificial Neural Network for Functions Approximation Using Particle Swarm Optimization
	1 Introduction
	2 Methodology
		2.1 Building a Feed Forward ANN
		2.2 Implementing the PSO Algorithm
	3 Results and Analysis
		3.1 Experimental Environment and Parameter Settings
		3.2 Experimental Results
		3.3 Limitations
	4 Conclusion
	References
Two Modified NichePSO Algorithms for Multimodal Optimization
	1 Introduction
	2 The NichePSO Algorithm
		2.1 Cognitive Velocity Update
		2.2 Social Velocity Update
		2.3 Initialization
		2.4 Partitioning Criteria
		2.5 Merging Subswarms
	3 The NichePSO-R Algorithm
	4 The NichePSO-S Algorithm
	5 Experimental Results
		5.1 Results
	6 Conclusions
	References
VaCSO: A Multi-objective Collaborative Competition Particle Swarm Algorithm Based on Vector Angles
	1 Introduction
	2 The Proposed VaCSO
		2.1 General Framework
		2.2 Clustering Based on Indicators
		2.3 Competitive Learning Based on Elite Archive Sets
		2.4 Co-Evolution Based on the ``Three-Particle Competition'' Mechanism
	3 Experimental Studies
		3.1 Experimental Parameter Settings
		3.2 Experimental Results and Analysis
	4 Conclusion and Remark
	References
The Experimental Analysis on Transfer Function of Binary Particle Swarm Optimization
	1 Introduction
	2 The Transfer Function of the BPSO
		2.1 The Conventional BPSO
		2.2 The Transfer Function of BPSO
		2.3 The Analysis on the Velocity of BPSO
	3 The Discussion of Transfer Function on BPSO
	4 Experiment Test with 0/1 Knapsack Problem
		4.1 The Description of MKP
		4.2 Experiment and Analysis
	5 Conclusion
	References
Multi-stage COVID-19 Epidemic Modeling Based on PSO and SEIR
	1 Introduction
	2 SEIR Modeling of COVID-19
		2.1 Data Sources
		2.2 Modified SEIR Model of COVID-19
	3 Parameter Estimation of the Model
		3.1 The PSO Algorithm
		3.2 Modified SEIR Model Optimized by PSO Algorithm
		3.3 Parameter Estimation and Analysis
	4 Conclusion
	References
Particle Swarms Reformulated Towards a Unified and Flexible Framework
	1 Introduction
		1.1 Trajectory Difference Equation
		1.2 Neighbourhood Topology
		1.3 Other Features
	2 Reformulated Particle Swarm Optimisation
	3 Global Features
		3.1 Initialisation
		3.2 Termination Conditions
	4 Individual Behaviour Features
		4.1 Deterministic Features
		4.2 Stochastic Features
	5 Social Behaviour Features
		5.1 Local Sociometry
		5.2 Current Information Update
		5.3 Memorised Information Update
	6 Conclusions
	References
Ant Colony Optimization
On One Bicriterion Discrete Optimization Problem and a Hybrid Ant Colony Algorithm for Its Approximate Solution
	1 Introduction
	2 Substantial Problem Statement
	3 Formal Problem Statement
	4 Hybrid Algorithm
	5 Example Problem ``data-j8-p2-r4"
	6 Test Results
	7 Conclusions
	References
Initializing Ant Colony Algorithms by Learning from the Difficult Problem’s Global Features
	1 Introduction
	2 Learning from the Global Features
		2.1 The Global Features of Solution Space
		2.2 Edge-Based Relative Frequency
	3 Initializing GFL-ACO
	4 Experimental Tests
	5 Conclusion
	References
An Ant Colony Optimization Based Approach for Binary Search
	1 Introduction
	2 Model of the System
	3 Ant Colony Optimization based Binary Search
	4 Case Study
		4.1 Existence of a Search Space in Which the Key Value May Be Found
		4.2 Non-existence of a Search Space
	5 Experimental Results
	6 Comparison Between ACOBS and Search Techniques
		6.1 Comparison Between ACOBS and Binary Search
		6.2 Comparison Between ACOBS and Sequential Search
		6.3 Time Complexity of ACOBS and Other Search Techniques
	7 Mathematical Model of the System
	8 Computational Complexity
		8.1 Successful Search Space
		8.2 Unsuccessful Search Space
	9 Conclusion
	References
A Slime Mold Fractional-Order Ant Colony Optimization Algorithm for Travelling Salesman Problems
	1 Introduction
	2 Related Work
		2.1 Ant Colony Optimization Algorithm
		2.2 Fractional-Order Calculus
		2.3 Slime Mold Model
	3 Algorithm Description
		3.1 Modified Slime Mold Model
		3.2 SMFACO State Transition Probability
		3.3 SMFACO Pheromone Updating Rule
	4 Experiments
		4.1 Experimental Settings
		4.2 Experimental Results and Analysis
	5 Conclusion
	References
Ant Colony Optimization for K-Independent Average Traveling Salesman Problem
	1 Introduction
	2 Problem Description
		2.1 K-Independent Average TSP
		2.2 K-Independent Total TSP
	3 K-Independent Average ACO
		3.1 Overview
		3.2 Simultaneous Movement of Ants
		3.3 Heuristic with Degree of Possible Options
		3.4 2-best-opt
		3.5 Pheromone Update
	4 Empirical Study
		4.1 Parameters and Settings
		4.2 Performance Evaluation of Heuristics
		4.3 Performance Evaluation of KI-Average-ACO
	5 Conclusions and Future Work
	References
Differential Evolution
Inferring Small-Scale Maximum-Entropy Genetic Regulatory Networks by Using DE Algorithm
	1 Introduction
	2 Maximum-Entropy GRNs
	3 Method
		3.1 Problem Formulation
		3.2 Strategy Selection: Probability Matching
		3.3 Parameter Adaptation
		3.4 Optimization Work Flow
	4 Experimental Results
		4.1 Simulation Studies
		4.2 Real Data Analysis
	5 Conclusion
	References
Variable Fragments Evolution in Differential Evolution
	1 Introduction
	2 Differential Evolution
		2.1 Generation of Initial Population
		2.2 Mutation Operator
		2.3 Crossover Operator
		2.4 Selection Operator
	3 Analysis of Crossover Operator in DE
	4 Variable Fragments Evolution in DE
		4.1 Variable Fragments Evolution
		4.2 DE with Variable Fragment Evolution
	5 Experimental Study
		5.1 Experimental Setup
		5.2 Results on Benchmark Functions
	6 Conclusions
	References
The Efficiency of Interactive Differential Evolution on Creation of ASMR Sounds
	1 Introduction
	2 Differential Evolution and Interactive Differential Evolution
		2.1 Differential Evolution (DE)
		2.2 Interactive Differential Evolution (IDE)
	3 IDE Creating ASMR Sounds
	4 Experimental Method
		4.1 Search Experiment
		4.2 Evaluation Experiment
	5 Experimental Results
		5.1 Result of Search Experiment
		5.2 Result of Evaluation Experiment
	6 Discussion
	7 Conclusion
	References
Genetic Algorithm and Evolutionary Computation
Genetic Algorithm Fitness Function Formulation for Test Data Generation with Maximum Statement Coverage
	1 Introduction
	2 Theoretical Background
		2.1 Genetic Algorithm for Test Data Generation
		2.2 Formulation of the Fitness Function for Maximum Statement Coverage
	3 Research
	4 Conclusion
	References
A Genetic Algorithm-Based Ensemble Convolutional Neural Networks for Defect Recognition with Small-Scale Samples
	1 Introduction
	2 Proposed GA-Based Ensemble CNNs
		2.1 Basic CNN Model
		2.2 GA for Ensemble Weight Optimization
		2.3 Application
	3 Experimental Results
		3.1 Experimental Setting
		3.2 Experimental Results
	4 Discussion
	5 Conclusion and Future Work
	References
Biased Random-Key Genetic Algorithm for Structure Learning
	1 Introduction
	2 Background
	3 Bayesian Network Structure Learning
		3.1 Problem Definition
		3.2 Implementation Process
	4 Experiment
		4.1 Experimental Parameters
		4.2 Experimental Results
		4.3 Analysis
	5 Conclusion
	References
Fireworks Algorithms
Performance Analysis of the Fireworks Algorithm Versions
	1 Introduction
	2 Fireworks Algorithm
	3 Deep Statistical Comparison
	4 Fireworks Algorithms Evaluation
	5 Conclusion
	References
Using Population Migration and Mutation to Improve Loser-Out Tournament-Based Fireworks Algorithm
	1 Introduction
	2 Related Work
		2.1 Explosion Operation
		2.2 Selection Operation
		2.3 Loser-Out Tournament-Based Fireworks Algorithm
	3 The Proposed Algorithm
		3.1 Biogeography-Based Optimization
		3.2 ILoTFWA
	4 Experiments
		4.1 Experimental Settings
		4.2 Experimental Results
	5 Conclusion
	References
Region Selection with Discrete Fireworks Algorithm for Person Re-identification
	1 Introduction
	2 Related Work
	3 Method
		3.1 A Subsection Sample
		3.2 Region Selecting with Discrete Fireworks Algorithm
	4 Experiment
	5 Conclusion
	References
Fireworks Harris Hawk Algorithm Based on Dynamic Competition Mechanism for Numerical Optimization
	1 Introduction
	2 Related Work
		2.1 Harris Hawk Algorithm
		2.2 The Explosive Operation of Fireworks Algorithm
	3 Proposed Algorithm: DCFW-HHO
		3.1 Dynamic Competition Mechanism
		3.2 Fireworks Harris Hawk Algorithm based on Dynamic Competition Mechanism (DCFW-HHO)
	4 Experiment and Result
		4.1 Benchmark Functions and Parameter Setting
		4.2 Numerical Experiment
		4.3 Converging Curves of the Average Best Fitness
	5 Conclusion
	References
Enhancing Fireworks Algorithm in Local Adaptation and Global Collaboration
	1 Introduction
	2 Backgrounds
		2.1 Problem Definition
		2.2 Fireworks Algorithms
		2.3 Related Works
	3 Proposed Strategies
		3.1 Adaptation
		3.2 Restart
		3.3 Collaboration
		3.4 Experiments
	4 Discussions
	5 Conclusion
	References
Brain Storm Optimization Algorithm
Multi-objective Brainstorming Optimization Algorithm Based on Adaptive Mutation Strategy
	1 Introduction
	2 The Basic Problem Description
		2.1 Multi-objective Optimization Problem
		2.2 Brainstorming Optimization Algorithm
	3 Multi-objective Brainstorming Optimization Algorithm Based on Adaptive Mutation Strategy
		3.1 Population Mutation
		3.2 Adaptation of Learning Factors
	4 Experiment
		4.1 Testing Proplems
		4.2 Parameter Setting
		4.3 Experimental Results and Analysis
	5 Conclusion
	References
Brain Storm Optimization Algorithm Based on Formal Concept Analysis
	1 Introduction
	2 Related Work
		2.1 Original Brain Storm Optimization Algorithm
		2.2 Formal Concept Analysis
	3 The Proposed Method
		3.1 Framework of HBSO
		3.2 Individual Similarity Analysis
		3.3 Adaptively Determine the Number of Clusters
	4 Experiments and Results
		4.1 Parameter Settings and Test Functions
		4.2 Result and Discussion
	5 Conclusion
	References
An Improved Brain Storm Optimization Algorithm Based on Maximum Likelihood Estimation
	1 Introduction
	2 Double Grouping
		2.1 Interaction Structure of the Decision Variables
		2.2 Double Grouping Strategy
	3 Creating Strategy Based on Maximum Likelihood Estimation
	4 Experimental Results and Analysis
		4.1 Complex Offset Test Functions and Parameter Settings
		4.2 Experimental Comparison
	5 Conclusion
	References
Bacterial Foraging Optimization Algorithm
Reorganized Bacterial Foraging Optimization Algorithm for Aircraft Maintenance Technician Scheduling Problem
	1 Introduction
	2 Model of Aircraft Maintenance Technician Scheduling Problem
		2.1 Problem Description
		2.2 Objective Function and Constraints
	3 Reorganized Bacterial Foraging Optimization Algorithm
		3.1 Structural Recombination
		3.2 Information Transmission Mechanism
	4 Experiments and Results
		4.1 Encoding Scheme
		4.2 Parameter Settings
		4.3 Experimental Results
	5 Conclusions and Future Directions
	References
A Bacterial Foraging Optimization Algorithm Based on Normal Distribution for Crowdfunding Project Outcome Prediction
	1 Introduction
	2 Methodology
		2.1 Light Gradient Boosting Machine
		2.2 Bacterial Foraging Optimization
		2.3 Enhanced LightGBM Framework with Improved BFO
	3 Experiments and Results
		3.1 Dataset
		3.2 Experiment Settings
		3.3 Experiment Results
	4 Conclusion and Future Work
	References
Bacterial Foraging Optimization with Leader Selection Strategy for Bi-objective Optimization
	1 Introduction
	2 Related Background
		2.1 Multi-objective Optimization
		2.2 Pareto Optimality
		2.3 Bacterial Foraging Optimization
	3 Bi-objective Bacterial Foraging Optimization
		3.1 Leader Selection Strategy
		3.2 Swarm Strategy
		3.3 External Archive Control
	4 Experiments and Results
		4.1 Problems and Algorithm Settings
		4.2 Results and Analysis
	5 Conclusions and Feature Work
	References
DNA Computing Methods
Stability and Hopf Bifurcation Analysis of DNA Molecular Oscillator System Based on DNA Strand Displacement
	1 Introduction
	2 Model Establishment
	3 Positive Boundedness of Solution
	4 Dynamic Analysis of Systems Without Time Delay
	5 Dynamic Analysis of Systems with Time Delay
	6 Hopf Bifurcation Direction
	7 Numerical Simulation
	8 Conclusion
	References
Dynamic Behavior Analysis of DNA Subtraction Gate with Stochastic Disturbance and Time Delay
	1 Introduction
	2 Preparation
	3 Existence and Uniqueness of the Positive Solution
	4 Stationary Distribution and Ergodicity
	5 Numerical Simulations
	6 Conclusions
	References
Modeling and Analysis of Nonlinear Dynamic System with Lévy Jump Based on Cargo Sorting DNA Robot
	1 Introduction
	2 Modeling of Nonlinear Biochemical Reaction System with Lévy Jump Based on Cargo Sorting DNA Robot
		2.1 Modeling of Nonlinear DNA Robot Reaction System
		2.2 Modeling of Nonlinear DNA Robot Reaction System with Lévy Jump
	3 The Existence and Uniqueness of Positive Solutions
	4 Sufficient Conditions for the End and Continuation of the Reaction
		4.1 Sufficient Conditions for the End of the Reaction
		4.2 Sufficient Conditions for Continuous Response
	5 Positive Recursion of Reaction
	6 Numerical Simulation
	7 Conclusions
	References
Stability and Hopf Bifurcation Analysis of Complex DNA Catalytic Reaction Network with Double Time Delays
	1 Introduction
	2 Modelling and Analysis of Complex DNA Catalytic Reaction Network System
		2.1 System Modelling of DNA Catalytic Reaction Network Using Toehold
		2.2 Double Time Delays System Modelling of DNA Catalytic Reaction Network
		2.3 Model Simplification
	3 Stability Analysis and Hopf Bifurcation of Complex DNA Catalytic Reaction Network System
	4 Numerical Simulation
	5 Conclusion
	References
Author Index