A human-machine cooperative approach for combinatorial optimization problem

Xueming Yan, Han Huang, Zhifeng Hao, Gang Li

Abstract: The human-computer cooperative approaches for handling the combinatorial optimization problems are introduced. In this paper we propose the human-computer cooperation approach for combinatorial optimization problems. Firstly, the initial solutions are seen as the sampling in human cognition by computer games. The games are developed for special combinatorial optimization problems. Then fuzzy decomposition decomposes the optimization problem into several sub-problems according to initial solutions by human. Moreover, local search strategy is given in conformational space with human strategy development capabilities, which also explores the space of possible search strategies. Last, the stochastic elements of the search in the traditional computational algorithms are gone with human intelligence during the fuzzy composition process. Human-computer cooperation approach can indeed lead to mutual advantage, and it can improve the problem-solving skills. We apply the proposed method to two-echelon vehicle routing problem to verify its effectiveness and usefulness.