An Improved Differential Evolution Algorithm for Mixed Integer Programming Problems
Jun Lang Wu, Gao Yue-lin, Yan Lina · 2013
This paper proposes an improved differential evolution algorithm, named I-DE, for constrained nonlinear mixed integer programming problems. The new population initialization technology and dynamic non-linear scaling factor are applied to enhance optimization capability of algorithm. We strengthen influence of constraint matrix to deal with constraint of problems. Introduction of special truncation procedure to handle integer restrictions and selection operator based on Deb constraint rules update the population. The test results show that the I-DE algorithm possess higher success rate and precision than MI-LXPM algorithm and has found solutions which are better than the known optimal solution in five problems.