An incorporated algorithm for combined heat and power economic dispatch

This paper presents an improved genetic algorithm with multiplier updating (IGA_MU) to solve the combined heat and power economic dispatch (CHPED) problem. The improved genetic algorithm (IGA) equipped with an improved evolutionary direction operator (IEDO) and a migration operation can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to avoid deforming the augmented Lagrange function and resulting in difficulty of solution searching. The proposed approach integrates the IGA and the MU such that it has the merits of automatically adjusting the randomly given penalty to a proper value and requiring only a small-size population for the CHPED problem. Extensive simulations using the proposed method are carried out on various-size systems, and the results are compared with that of the previous methods. Numerical results indicate that the proposed approach has more advantages than other methods in application. Moreover, the proposed algorithm provides an efficacious approach for large-scale systems of the CHPED problem. (C) 2003 Elsevier B.V. All rights reserved.