Evolutionary Computation for Manufacturing Optimisation: Recent Developments
Christos D. Dimopoulos, Ali M. S. Zalzala · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 1998
Genetic Algorithms (GA's) were formally introduced by Holland (10 more than twenty years ago. Since then, numerous algorithms based on the concept of Darwinian strife for survival have been developed and applied to a large number of optimisation problems. The operation of a simple GA is straightforward: Given a certain optimisation problem, an initial population of binary-coded solutions (chromosomes) is generated randomly. The performance of each solution is evaluated and assigned a "fitness" value. A new population is then created, by evolving chromosomes selected from the old population. The higher the "fitness" of an individual solution, the better its chance to be selected for the new population........