| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNISA996647866603316 |
|
|
Autore |
Singh Hemant |
|
|
Titolo |
Evolutionary Multi-Criterion Optimization : 13th International Conference, EMO 2025, Canberra, ACT, Australia, March 4–7, 2025, Proceedings, Part I / / edited by Hemant Singh, Tapabrata Ray, Joshua Knowles, Xiaodong Li, Juergen Branke, Bing Wang, Akira Oyama |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
|
|
Edizione |
[1st ed. 2025.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (498 pages) |
|
|
|
|
|
|
Collana |
|
Lecture Notes in Computer Science, , 1611-3349 ; ; 15512 |
|
|
|
|
|
|
Altri autori (Persone) |
|
RayTapabrata |
KnowlesJoshua |
LiXiaodong |
BrankeJuergen |
WangBing |
OyamaAkira |
|
|
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Artificial intelligence |
Artificial Intelligence |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
-- Algorithm design. -- Towards an Efficient Innovation Path Seeking Algorithm Using Directed Domination. -- An MaOEA/Local Search Hybrid Based on a Fast, Stochastic BFGS Using Achievement Scalarizing Search Directions. -- Selective evaluations for expediting multi-objective bilevel optimization. -- MOAISDX: A New Multi-objective Artificial Immune System based on Decomposition. -- PAES-25: Local Search, Archiving and Multi/Many-objective PseudoBoolean Functions. -- Weights-Guided Random Bit Climber for Binary Many-objective Optimization. -- Bilevel Optimization-based Decomposition for Solving Single and Multi objective Optimization Problems. -- A Study on Optimistic & Pessimistic Pareto-fronts in Multi objective Bilevel Optimization via ?-Perturbation. -- Cumulative Step Size Adaptation for Adaptive SEMO in Integer Space. -- Adaptive Normal-Boundary Intersection Directions for Evolutionary Many objective Optimization |
|
|
|
|
|
|
|
|
|
|
|
with Complex Pareto Fronts. -- Encodings for Multi-Objective Free-Form Coverage Path Planning. -- VBEA: Voting-Based Evolutionary Algorithm for Multi-Objective Planning. -- Enhancing NSGA-II with a Knee Point for Constrained Multi-objective Optimization. -- Benchmarking. -- Single and Multi-Objective Optimization Benchmark Problems Focusing on Human-Powered Aircraft Design. -- An Extension of the Welded Beam Problem that Includes Multiple Interactng Design Concepts. -- Extended Results on Analytical Hypervolume Indicator Calculation of Linear and Quadratic Pareto Fronts. -- MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOH profiler. -- Applications. -- Multi-Objective Sequential Decision Making for Holistic Supply Chain Optimization. -- Interactive evolutionary re optimization for ground fish survey planning. -- A Multi-Objective Competitive Co-Evolutionary Framework with Progressive Shrinking for Wargame Scenarios. -- -- Impact of Environmental Changes on Optimized Robotics Collective Motion for Multi-Objective Coverage Tasks. |
|
|
|
|
|
|
Sommario/riassunto |
|
This two-volume set LNCS 15512-15513 constitutes the proceedings of the 13th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2025, held in Canberra, ACT, Australia, in March 2025. The 38 full papers and 2 extended abstracts presented in this book were carefully reviewed and selected from 63 submissions. The papers are divided into the following topical sections: Part I : Algorithm design; Benchmarking; Applications. Part II : Algorithm analysis; Surrogates and machine learning; Multi-criteria decision support. |
|
|
|
|
|
|
|
| |