Computational Intelligence in Optimization

This collection of recent studies spans a range of computational intelligence applications, emphasizing their application to challenging
real-world problems. Covers Intelligent agent-based algorithms, Hybrid intelligent systems, Machine learning and more.

State of the art of applications and implementations of computational intelligence in optimization

Systolic VLSI and FPGA Realization of Artificial Neural Networks.- The structure and use of opposition for decreasing function evaluations in population-based search.- A Review of Agent-Based Co-Evolutionary Algorithms for Multi-Objective Optimization.- New Hybrid Intelligent Systems to Solve Linear and Quadratic Optimization Problems and Increase Guaranteed Optimal Convergence speed of Recurrent ANN.- Optimization problems with cardinality constraints.- From Simulation to Hardware: Towards Real-World Implementation of Evolvable Neural Network-Based Multirobot Controllers.- Optimization with Clifford Support Vector Machines and applications.- A Classification method based on principle component analysis and differential evolution algorithm applied for prediction diagnosis from clinical EMR heart data bases.- Railway Timetable Problems.- Learning to Optimize: Intelligent Global Optimization using Support Vector Machines.- Project Scheduling: Time-cost tradeoff problems.- A Game Theory-Based Multi-Agent System for Expensive Optimisation Problems.- Search Procedure Exploiting Local Regularized Objective Approximation (SPELROA).