An Evolutionary Programming to Solve Constrained Optimization Problems

A mixed strategies evolutionary programming to solve constrained optimization problems is presented in this paper. The approach does not require the use of a penalty function. Instead, it uses a diversity conservation mechanism based on allowing infeasible solutions to remain in the population. A mixed mutation strategy and feasibility-based comparison mechanism is used to guide the process fast toward the feasible region of the search space. This new evolutionary programming has been tested on 13 benchmark functions. The results obtained show that the new approach is a general and effective method.