Modeling and Solution Algorithm for Fourth-Party Logistics Routing Problem Based on Service Composition

Aiming at the problems of limited transportation resources and high transportation costs of a single third-party logistics supplier, our research proposes a route planning model based on service combination from the perspective of fourth-party logistics, which aims to find the route with minimum total cost under the premise of meeting customer needs. In order to improve solution efficiency, a specific genetic algorithm is designed. The algorithm adopts backtracking idea and adaptive operations, which can avoid infeasible solution caused by strict constraints, while reducing the time required for crossover and mutation operations to repair infeasible solutions. In addition, Dijkstra-based heuristic algorithm, traditional genetic algorithm and traditional ant colony algorithm are implemented. The comparison of computational experiments on different scales instances shows that the specific genetic algorithm can obtain the optimal solution in small-scale instances, and the solution quality in large-scale problems is better than other algorithms.