Abstract
This paper proposes a versatile heuristic solution algorithm for nonlinear programming problems. Differential Evolution (DE), proposed by Storn et al., has the following two issues: one is that the algorithm has a tendency to fall into a local optimal solution, and the other is that the algorithm cannot be applied to nonlinear programming problems with constraints directly. For searching widely in a feasible set, the movement of individuals and their evaluation function are improved. The efficiency of the solution algorithm is shown by applying it to various types and scales of non-linear programming problems.
