Model and Algorithm for Fourth Party Logistics Routing Optimization Problem Based on Cumulative Prospect Theory

Considering the effect of customer risk preference on fourth party logistics routing optimization (4PLRP), the customers’ behavioral factors are introduced into decision making, and a method based on the cumulative prospect theory to solve the 4PL routing optimization is proposed. The method uses the prospect value of cumulative prospect theory as the customers’ utility function and the optimal objective to formulate the evaluation function of the improved ant colony algorithm, and the hybrid behavior based ant colony algorithm (HBACA) is used to solve the optimal logistics route. Analysis is made through comparing models based on expected utility maximization and prospect theory. Simulation and experimental data indicate that this method obtains high customer satisfaction, so the model and algorithm are proved to be effective and feasible.