关键词: 局部邻域搜索, 逆梯度, 局部极值点, 禁忌邻域, 换热网络

Abstract: The local neighborhood search methods depend greatly on the initial solution position and are usually subjected to the local optimal solutions. Therefore, an inverse gradient evolution algorithm with penalty is proposed in this paper. This algorithm employs a penalty positively related to the dwell time at the local optimal position to force the individual to move along the inverse gradient direction and then far away from the current local optimum. Meanwhile, to prevent 'rebound' phenomenon, tabooed neighborhood is introduced into the algorithm to prohibit the individual from moving back to its original position. As the filled functions are established by penalty in real-time, the mechanism of escaping the local optima in the proposed method is relatively deterministic rather than random in the heuristic methods, which improves the search efficiency for the individual. Finally, applying the algorithm to heat exchanger network synthesis problems, its effectiveness is verified by the typical 10SP1 and 10SP2 case studies. The obtained solutions are better than those in the literature, demonstrating the relatively strong ability of the proposed method to jump out of local optima.

Key words: local neighborhood search, inverse gradient, local optima, tabooed neighborhood, heat exchanger network