A new heuristic algorithm with the step size adjustment strategy for heat exchanger network synthesis

The major difficulty in the heat exchanger network synthesis (HENS) is dealing with the simultaneous optimization of large-scale continuous and integer variables. Heuristic algorithms are used in HENS due to their efficient global search ability and the step size (ΔL) constitutes one of the critical concepts in it. In this paper, by analyzing the influence of ΔL in Random Walk Algorithm with Compulsive Evolution (RWCE), it was pronounced that evolution speed got faster when ΔL increased in the early stage and evolution accuracy was higher by ΔL declination, in the late stage. Hence, five new different ΔL adjustment functions were proposed. This case-study concluded that ΔL adjustment functions in an upward parabola declination could maintain high speed in the early stage and improve the accuracy of solutions in late stage respectively. However, during the late stage, the minor ΔL led to the decline of the global search ability and it was difficult to jump out of the local minimum. Furthermore certain individuals in the population were randomly given a relatively large ΔL in late stage. Thus, an integrated RWCE algorithm with ΔL adjustment strategy was presented and demonstrated satisfying global and local search ability.