Advances in swarm intelligence : 12th International Conference, ICSI 2021, Qingdao, China, July 17-21, 2021, Proceedings. Part II / Ying Tan, Yuhui Shi (eds.).

Intro -- Preface -- Organization -- Contents -- Part II -- Contents -- Part I -- Multi-objective Optimization -- A Multi-objective Evolutionary Algorithm Based on Second-Order Differential Operator -- 1 Introduction -- 2 MOP Problem -- 3 Second-Order Differential Evolution -- 4 MOEA/D-SODE Algorithm -- 4.1 General Framework of MOEA/D-SODE -- 4.2 A SODE-Best Second-Order Differential Operator -- 4.3 The Flow Chart of MOEA/D-SODE -- 5 Experimental Results and Analysis -- 5.1 Experimental Environment and Parameter Setting -- 5.2 Performance Metrics -- 5.3 Analysis of Experimental Results

6 Conclusion -- References -- An Improved Evolutionary Multi-objective Optimization Algorithm Based on Multi-population and Dynamic Neighborhood -- 1 Introduction -- 2 Problem Statement and Related Methods -- 2.1 Problem Statement -- 2.2 Related Methods -- 3 Proposed Method -- 3.1 Framework of the Proposed Method -- 3.2 Multi-population Strategy -- 3.3 Dynamic Neighborhood -- 4 Experiment and Analysis -- 4.1 Settings -- 4.2 Results and Analysis -- 5 Conclusion -- References -- A Multiobjective Memetic Algorithm for Multiobjective Unconstrained Binary Quadratic Programming Problem

1 Introduction -- 2 Background -- 2.1 Multiobjective Optimization -- 2.2 Formulation of mUBQP -- 3 Proposed Algorithm: MOMA -- 3.1 Framework of MOMA -- 3.2 Population Initialization and Stopping Criterion -- 3.3 Uniform Generation -- 3.4 Crossover Operator and Tabu Search -- 3.5 Archive and Weight Vector Updating -- 4 Computational Experiments -- 4.1 Experimental Settings and Performance Measures -- 4.2 Competitors -- 4.3 Comparing MOMA with the Competitors -- 5 Conclusion and Future Work -- References

A Hybrid Algorithm for Multi-objective Permutation Flow Shop Scheduling Problem with Setup Times -- 1 Introduction -- 2 Problem Description -- 3 Proposed Hybrid Algorithm for Multi-objective PFSP with Setup Times -- 3.1 Encoding and Decoding of Chromosome -- 3.2 Initial Population Generation -- 3.3 Pareto Sorting -- 3.4 Selection and Crossover Operator -- 3.5 Mutation Operator -- 3.6 Neighborhood Structure Design -- 3.7 Flowchart of Proposed MOHGA -- 4 Experimental Results and Analysis -- 5 Conclusion and Future Work -- References

Dynamic Multi-objective Optimization via Sliding Time Window and Parallel Computing -- 1 Introduction -- 2 Background -- 2.1 Dynamic Multi-objective Optimization -- 2.2 Performance Metric -- 2.3 Sliding Time Window -- 3 Related Work -- 4 Sliding Time Window Based on Parallel Computing -- 5 Experimental Results and Analyses -- 5.1 Test the STW-PC Using MIGD -- 5.2 Experimental Analysis -- 6 Conclusions and Future Work -- References -- A New Evolutionary Approach to Multiparty Multiobjective Optimization -- 1 Introduction -- 2 Related Work

2.1 Multiparty Multiobjective Optimization Problems (MPMOPs).

Includes author index.

This two-volume set LNCS 12689-12690 constitutes the refereed proceedings of the 12th International Conference on Advances in Swarm Intelligence, ICSI 2021, held in Qingdao, China, in July 2021. The 104 full papers presented in this volume were carefully reviewed and selected from 177 submissions. They cover topics such as: Swarm Intelligence and Nature-Inspired Computing; Swarm-based Computing Algorithms for Optimization; Particle Swarm Optimization; Ant Colony Optimization; Differential Evolution; Genetic Algorithm and Evolutionary Computation; Fireworks Algorithms; Brain Storm Optimization Algorithm; Bacterial Foraging Optimization Algorithm; DNA Computing Methods; Multi-Objective Optimization; Swarm Robotics and Multi-Agent System; UAV Cooperation and Control; Machine Learning; Data Mining; and Other Applications.

Online resource; title from PDF title page (SpringerLink, viewed July 21, 2021).