Multi-objective optimization of stochastic demand inventory routing problem with time windows

作者：Lü Xiongwei; Li Jun^*; Lei Ming; Zhang Bin

来源：Journal of Southwest Jiaotong University, 2009, 44(2): 289-294.

DOI：10.3969/j.issn.0258-2724.2009.02.027

• Adaptive strategies
• Best choices
• Convergence speed
• Distribution strategies
• Genetic operators
• Global optimal solutions
• Inventory routing problem
• Local searches
• Low costs
• Multi objectives
• Multi-objective genetic algorithm
• Multi-objective optimizations
• Optimal schemes
• Optimization models
• Product distribution systems
• Stochastic demand
• Time window

An optimization model for multi-objective inventory and distribution strategies was established to solve the stochastic demand inventory routing problem with time windows (IRPTW). The model was solved with a multi-objective genetic algorithm (GA). The algorithm uses such genetic operators as best choice and adaptive strategy to approach the global optimal solution. It overcomes the inability of conventional GA in local search, increases convergence speed, and improves global optimization performance. A product distribution system of a logistic company was taken as an example, and the result shown that an optimal scheme with a reasonably low cost was obtained with the algorithm.

• 出版日期2009
• 单位西南交通大学