Previous studies on the fourth party logistics (4PL) routing problem have given little consideration to the risk preference of customer. Considering the customer"s risk preference, the value function in prospect theory is used to measure the customer"s risk attitude towards distribution cost and delivery period, and establish a mathematical model to maximize the utility of customer psychology evaluation. According to the characteristics of logistics network path optimization, an adaptive genetic algorithm embedded in Dijkstra algorithm is designed to solve the problem. Several numerical examples with different scales are designed, and the feasibility and effectiveness of the model and algorithm are illustrated on the basis of the simulation experiments. This paper provides a new decision-making model and optimization method for solving the fourth party logistics path optimization problem from the perspective of the influence of behavior on decision-making results.