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.Contents: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 papersReadership: Academics, researchers, practitioners and postgraduates students in operations research and engineering.