Logistics distribution problem is an important part of the modern logistics system. Suppliers need to plan a route scheme for each customer in goods distribution, which is a multi-ponit to multi-point problem. It is NP-hard.Through analysis of characteristics of the existing logistics system, mathematical models are constructed, by introducing the order request and the return request with multiple suppliers. With these models, we present  multi-vendor logistics distribution optimized algorithm and heuristic logistics distribution algorithm based on parallel multi-colonies. The first algorithm takes into account customer requests, make full use of vehicle loading and reasonably choose delivery route, so that transportation costs are lower, but the time cost is higher. The second algorithm add heuristic facor and introduce metrizable ratio, which get a faster convergence rate and higher-quality global optima. Simulation results show that both of the proposed algorithms can be adapted to this problem, but the heuristic logistics distribution algorithm based on parallel multi-colonies is more effective, which can keep balance between the time overhead and the best route.

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Airport ground services management are about the scheduling of each airport ground services equipment for the purpose of improving traffic control services, strengthening the operation and management, ensuring the normal operation of flights. We define a function of staff number and work time and establ;ish a mathematical model. And the random weight method is introduced to solve this multi-objective optimization problem what we establish. Based on the model, we present multi-population co-evolutionary Memetic algorithm. Simulation results show that the algorithm for the airport ground services problem is more effective.