Genetic algorithms are founded upon the principle of evolution‎,‎ i‎.‎e‎.‎‎,‎ survival of the fittest‎.‎ Hence evolution programming techniques‎,‎ based on genetic algorithms‎,‎ are applicable to many hard optimization problems‎,‎ such as optimization of functions with linear and nonlinear constraints‎,‎ the traveling salesman problem‎,‎ and problems of scheduling‎,‎ partitioning‎,‎ and control‎.‎ The importance of these techniques is still growing‎,‎ since evolution programs are parallel in nature‎,‎ and parallelism is one of the most promising directions in computer science‎.‎The book is self‎-contained and the only prerequisite is basic undergraduate mathematics‎.‎ This third edition has been substantially revised and extended by three new chapters and by additional appendices containing working material to cover recent developments and a change in the perception of evolutionary computation‎.‎