基于多阶段模糊规模效应量化的TMC模式下供应链调度优化研究

旅游大规模定制(Tourism Mass Customization, TMC)模式实施的关键是通过对旅游供应链的调度优化处理旅游活动的“规模效应”与游客“个性化需求”之间的矛盾问题。运用经济学及模糊数学的理论方法分析并实现了TMC模式下存在的多阶段模糊规模效应量化处理。构建了引入规模效应量化的服务成本最小化、引入模糊时间窗的顾客满意度最大化及供应链协同度最大化为优化目标的TMC模式下多目标供应链调度优化模型。最后,通过蚁群算法实现TMC模式下多调度优化目标的求解并对优化效果进行对比研究。研究结果表明,TMC模式下供应链调度中旅游活动存在多阶段模糊规模效应并且可以量化处理;TMC模式中的规模效应具有合理的区间范围,旅游企业应注重规模效应与其他目标的均衡;蚂蚁算法在求解TMC模式下多目标优化问题方面不仅收敛速度快,而且通过对多调度目标优化效果的对比检验表明,性能稳健优良。

Research on Supply Chain Scheduling Optimization under TMC Mode Basedon Multistage Fuzzy Scale Effect Quantification

The key of the implementation of Tourism Mass Customization is to deal with the contradiction between the “scale effect” of tourism activities and the “personalized demand” of tourists through the scheduling of tourism supply chain. Based on the theory of economics and fuzzy mathematics, we analyse and deal with the multistage fuzzy scale effect under TMC mode. The multi-objective supply chain scheduling optimization model is built under TMC mode, which includes the minimization of service cost based on scale effect quantification, the maximization of the customer satisfaction based on the fuzzy time window and the maximization of the supply chain synergy. Finally, ant colony algorithm is applied to solve the problem of multi-objective scheduling optimization under TMC mode, and the optimization effect is compared. The research results show that there exists multistage fuzzy scale effect in TMC scheduling, and it can be quantified; The scale effect of TMC mode has a reasonable interval range. Tourism enterprises should pay attention to the balance between scale effect and other goals; Ant algorithm not only has fast convergence speed in solving the multi-objective optimization problem in TMC mode, but also shows that the algorithm can quickly achieve multi-objective optimization and excellent performance.