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International Workshop on Big Optimization 2025 / edited by Christian Blum, Claudia Cavallaro, Carolina Crespi, El-Ghazali Talbi.
Springer eBooks EBA - Intelligent Technologies and Robotics Collection 2026 Available online
View online- Format:
- Book
- Author/Creator:
- Blum, C. (Christian)
- Series:
- Studies in Big Data, 2197-6511 ; 186
- Language:
- English
- Subjects (All):
- Engineering--Data processing.
- Engineering.
- Computational intelligence.
- Artificial intelligence.
- Data Engineering.
- Computational Intelligence.
- Artificial Intelligence.
- Local Subjects:
- Data Engineering.
- Computational Intelligence.
- Artificial Intelligence.
- Physical Description:
- 1 online resource (322 pages)
- Edition:
- 1st ed. 2026.
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2026.
- Summary:
- This volume explores innovative approaches to large-scale and high-dimensional optimization in the age of artificial intelligence, fostering collaboration between researchers and practitioners across disciplines. It emphasizes heuristic, metaheuristic, and hybrid strategies to address complex, data-intensive problems. The International Workshop on Big Optimization (WBO 2025) was held from July 31 to August 1, 2025, at the Department of Mathematics and Computer Science of the University of Catania, Italy. The book includes selected peer-reviewed papers of WBO 2025 covering topics such as combinatorial optimization, reinforcement learning, and AI-assisted decision-making, highlighting advances in intelligent and data-driven optimization. It is intended for researchers, professionals, and graduate students interested in the latest trends and methodologies shaping the future of optimization and AI.
- Contents:
- NeurOptimiser A General Framework for Neuromorphic Optimisation
- A Tabu Search Algorithm for the p Next Center Problem with Capacity and Coverage Radius Constraints
- Reactive Tabu Search for MAX SAT an Analysis of Sampling Strategies, etc.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 3-032-15455-3
- 9783032154552
- OCLC:
- 1572201405
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