Contemporary Advancement in Evolutionary Multi-objective Optimization (Genetic and Evolutionary Computation)

Mukhopadhyay, Somnath (EDT)/ Sarkar, Sunita (EDT)/ Deb, Kalyanmoy (EDT)

Springer Verlag, Singapore（2026/04発売）

• 製本 Hardcover:ハードカバー版
• 言語 ENG
• 商品コード 9789819579075

Full Description

This endeavour presents a rich collection of contemporary advances in evolutionary multi-objective optimisation algorithms, blending foundational concepts with state-of-the-art research and real-world applications. Featuring contributions from leading experts, it offers clear insights into modern EMO methodologies, emerging AI-EC integrations, and diverse problem-solving domains. An essential reference for researchers, practitioners, and students exploring intelligent optimisation Algorithms. 

Contents

"Balancing exploration-exploitation using Switching Mechanism Integrated with Adaptive Heterogeneous Comprehensive Learning PSO and L-SHADEBalancing exploration-exploitation using Switching Mechanism Integrated with Adaptive Heterogeneous Comprehensive Learning PSO and L-SHADE".- "Evolutionary Multi- and Many-objective Optimization: Enhancements using Machine Learning".- "A Many-Objective Optimized Folded Cross Regression Model (FCRM) with Unspecified Targets: A Critical Analysis".- "Emerging Techniques for Evolutionary Single- and Multi-Objective Optimization with Application to Humanoid Robot Gait Generation".- "Optimization models in Nurse Scheduling - A Review of last five years".- "A Review of Bilevel Optimization Methods, Emerging Applications, and Recent Advancements".- "A Review of Advances in Multi-Objective Optimization for Facility Location Problems".- "A Survey on Recent Advances in Multiobjective Evolutionary Clustering".