Abstract: Aiming at the logistics planning optimization problem for strategic alliance supply chain under multiple uncertainty, considering market demands and prices of finished product as random variables, a integrated logistics planning model for three-level, multi-node and multiple products strategic supply chain alliance is developed base on stochastic expected value programming theory. For this model a hybrid intelligence algorithm is designed based on random simulation. The effectiveness of the model and algorithm is illustrated with numerical examples simulation, and the sensitivity of parameters is analyzed. The experimental results show that the new developed model is effective and can provide theoretic basis and practical guide for logistics planning for strategic alliance supply chain, the algorithm is not entirely dependent on parameter values, the algorithm has stronger robustness, and the results of sensitivity analysis can be foundation for parameters’ control of the model.

Key words: strategic alliance supply chain;logistics planning;multiple uncertainty;model and algorithm;sensitivity analysis