{"product_id":"9783032135889","title":"Optimization and Learning : 8th International Conference, OLA 2025, Dubai, United Arab Emirates, April 23-25, 2025, Revised Selected Papers (Communications in Computer and Information Science 2808) (2026. xiv, 398 S. XIV, 398 p. 134 illus., 111 illus. in","description":"\u003cp\u003eThis book constitutes the refereed proceedings of the 8th International Conference on Optimization and Learning, OLA 2025, held in Dubai, United Arab Emirates, during April 23 25, 2025.\u003c\/p\u003e\u003cp\u003eThe 30 full papers presented here were carefully reviewed and selected from 70 submissions. They were organized in the following topical sections: Soft Computing and Machine Learning Advanced Models; Optimization and Search Algorithms: Metaheuristics and Hybrid Approaches; Modelling, Simulation and Complex Systems; Applications in Industry and Cibersecurity.\u003c\/p\u003e \u003cstrong\u003e.- Soft Computing and Machine Learning Advanced Models.\u003c\/strong\u003e.- KAN-based On-policy PPO Method for Continuous Reinforcement Learning. .- Bayesian and Partition-Based Optimization for Hyperparameter Optimization of LLM Fine-Tuning..- On hyperparameter Optimization of Generative Models in Recommendation Systems: a comparative study, and applications..- Enhancing AutoML with Algorithm Selection: A Path to Bette Performance..- NEVA: A Neuromorphic Evolutionary Algorithm..- Enhancing Academic Advising with AI: Leveraging Large Language Models and Retrieval-Augmented Generation for Smarter Student Support..- Overlay_dx- Automating forecasting evaluation..- Integrated Deep Learning Approaches for Coral Health Monitoring and Database Development.\u003cstrong\u003e.- Optimization and Search Algorithms: Metaheuristics and Hybrid Approaches.\u003c\/strong\u003e.-  Chaotic Binarization of Tasmanian Devil Optimization for Solving the Knapsack Problem..- Mother Tree Optimization Algorithm for Feature Selection..- An Improved NSGA-III Algorithm for Solving High-dimensional Many-objective Flexible Job Shop Scheduling Problem..- Adaptive Greedy Heuristic Algorithm for Rubber Tyred Gantry Crane Scheduling Problem at Container Terminal..- Solving the Electricity Technician Dispatch Problem..- Exact versus Bio-Inspired Approximation Methods for Solving Constrained CP-nets..- Dependent Task Offloading in Cloud-Edge-End Environments with Communication Heterogeneity.\u003cstrong\u003e.- Modelling, Simulation and Complex Systems.\u003c\/strong\u003e.- Modeling Trust Dynamics on a Multi-Agent System..- Knowledge Management Methodology for Complex context. The Defence case..- Exhaustive Search for Quantum Circuit Optimization using ZX Calculus..- Almost Linear Time Consistent Mode Estimation and Quick Shift Clustering..- Addressing classic Constraint Satisfaction Problems through Optimisation Modulo Theories..- Chance Constrained Optimization with Complex Variables..- Optimizing Retail Promotions with Mixed-Integer Nonlinear XI Programming and Cross-Elasticity Effects..- Solving the Semivectorial Bilevel Hazmat Network Design Problem by a Deconstructive Heuristic Algorithm.\u003cstrong\u003e.- Applications in Industry, Energy and Supply Chain.\u003c\/strong\u003e.- Evolutionary Techniques for Combinatorial Reverse Auctions in Electricity Consumption..- Optimizing and Reducing Changeover Time to Enhance Line Balancing in Industrial Injection Processes..- A Hybrid Approach for Pallet Loading in Ceramic Tile Industry..- A Comparative Analysis of the Algorithm Results for Designing Two-stage Supply Chains with Fixed Costs..- Optimizing Supplier Performance: Advanced Analytics and Predictive Modeling Approaches..- Systematic Review of Mac","brand":"SPRINGER, BERLIN; SPRINGER","offers":[{"title":"Default Title","offer_id":49902491140344,"sku":"00000_00000_00000_00000","price":166.44,"currency_code":"AUD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/8208\/6904\/files\/9783032135889-1.jpg?v=1783773234","url":"https:\/\/kinokuniya.com.au\/products\/9783032135889","provider":"Books Kinokuniya Australia","version":"1.0","type":"link"}