Description
Book SynopsisThis 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.
Table of ContentsHybrid 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.
