【摘要】 通过融合机会约束优化策略与序贯决策方法,提出了机会约束序贯优化策略。该策略在优化随机性VRP的决策中不但可以利用计算机的优化计算能力,而且可以将决策人的经验和偏好融入其中,这种人为参与的决策可以成功地解决随机性VRP的决策问题,避免了马尔科夫决策过程中存在的维数灾难问题。通过仿真模型对该策略的实验表明随机性VRP的序贯优化策略优于其它策略。更多还原

【Abstract】 By merging the chance constraint optimization strategy and the sequential optimization strategy, the Chance Constraint Sequential Optimization Strategy was proposed. The strategy, utilizing both the capacity of computer optimization and human intelligence of the decision maker, could solve the SVRP successfully and avoid the difficulty in Markov Decision Programming. The simulation results show that the strategy is superior to others in solving SVRP.更多还原