Continuous optimization is the study of problems in which we wish to opti- mize (either maximize or minimize) a continuous function (usually of several variables) often subject to a collection of restrictions on these variables. It has its foundation in the development of calculus by Newton and Leibniz in the 17*^ century. Nowadys, continuous optimization problems are widespread in the mathematical modelling of real world systems for a very broad range of applications. Solution methods for large multivariable constrained continuous optimiza- tion problems using computers began with the work of Dantzig in the late 1940s on the simplex method for linear programming problems. Recent re- search in continuous optimization has produced a variety of theoretical devel- opments, solution methods and new areas of applications. It is impossible to give a full account of the current trends and modern applications of contin- uous optimization. It is our intention to present a number of topics in order to show the spectrum of current research activities and the development of numerical methods and applications.

Continuous optimization is the study of problems in which we wish to opti­ mize (either maximize or minimize) a continuous function (usually of several variables) often subject to a collection of restrictions on these variables. It has its foundation in the development of calculus by Newton and Leibniz in the 17*^ century. Nowadys, continuous optimization problems are widespread in the mathematical modelling of real world systems for a very broad range of applications. Solution methods for large multivariable constrained continuous optimiza­ tion problems using computers began with the work of Dantzig in the late 1940s on the simplex method for linear programming problems. Recent re­ search in continuous optimization has produced a variety of theoretical devel­ opments, solution methods and new areas of applications. It is impossible to give a full account of the current trends and modern applications of contin­ uous optimization. It is our intention to present a number of topics in order to show the spectrum of current research activities and the development of numerical methods and applications.

Surveys.- Linear Semi-infinite Optimization: Recent Advances.- Some Theoretical Aspects of Newton’s Method for Constrained Best Interpolation.- Optimization Methods in Direct and Inverse Scattering.- On Complexity of Stochastic Programming Problems.- Nonlinear Optimization in Modeling Environments.- Supervised Data Classification via Max-min Separability.- A Review of Applications of the Cutting Angle Methods.- Theory and Numerical Methods.- A Numerical Method for Concave Programming Problems.- Convexification and Monotone Optimization.- Generalized Lagrange Multipliers for Nonconvex Directionally Differentiable Programs.- Slice Convergence of Sums of Convex functions in Banach Spaces and Saddle Point Convergence.- Topical Functions and their Properties in a Class of Ordered Banach Spaces.- Applications.- Dynamical Systems Described by Relational Elasticities with Applications.- Impulsive Control of a Sequence of Rumour Processes.- Minimization of the Sum of Minima of Convex Functions and Its Application to Clustering.- Analysis of a Practical Control Policy for Water Storage in Two Connected Dams.

Continuous optimization is the study of problems in which we wish to opti­ mize (either maximize or minimize) a continuous function (usually of several variables) often subject to a collection of restrictions on these variables. It has its foundation in the development of calculus by Newton and Leibniz in the 17*^ century. Nowadys, continuous optimization problems are widespread in the mathematical modelling of real world systems for a very broad range of applications. Solution methods for large multivariable constrained continuous optimiza­ tion problems using computers began with the work of Dantzig in the late 1940s on the simplex method for linear programming problems. Recent re­ search in continuous optimization has produced a variety of theoretical devel­ opments, solution methods and new areas of applications. It is impossible to give a full account of the current trends and modern applications of contin­ uous optimization. It is our intention to present a number of topics in order to show the spectrum of current research activities and the development of numerical methods and applications.