edited by I D L Bogle (University College London, UK) & J žilinskas (Institute of Mathematics and Informatics, Lithuania)

Table of Contents (57k)
Preface (55k)
Chapter 1: Hybrid Methods for Optimisation (520k)

This book covers different topics on optimal design and operations with particular emphasis on chemical engineering applications. A wide range of optimization methods — deterministic, stochastic, global and hybrid — are considered.

Containing papers presented at the bilateral workshop by British and Lithuanian scientists, the book brings together researchers' contributions from different fields — chemical engineering including reaction and separation processes, food and biological production, as well as business cycle optimization, bankruptcy, protein analysis and bioinformatics.

• Hybrid Methods for Optimisation (E S Fraga)
• An MILP Model for Multi-Class Data Classification (G Xu & L G Papageorgiou)
• Studying the Rate of Convergence of the Steepest Descent Optimisation Algorithm with Relaxation (R J Haycroft)
• Optimal Estimation of Parameters in Market Research Models (V Savani)
• A Redundancy Detection Approach to Mining Bioinformatics Data (H Camacho & A Salhi)
• Optimal Open-Loop Recipe Generation for Particle Size Distribution Control in Semi-Batch Emulsion Polymerisation (N Bianco & C D Immanuel)
• Multidimensional Scaling Using Parallel Genetic Algorithm (A Varoneckas et al.)
• Evaluating the Applicability of Time Temperature Integrators as Process Exploration and Validation Tools (S Bakalis et al.)
• Optimal Deflection Yoke Tuning (V Vaitkus et al.)
• and other papers