计算机集成制造系统 ›› 2018, Vol. 24 ›› Issue (第11): 2867-2878.DOI: 10.13196/j.cims.2018.11.021

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需求异质性下的定制化自提点服务组合优化

韩珣1,张锦1,2,崔异1+   

  1. 1.西南交通大学交通运输与物流学院
    2.西南交通大学综合交通运输智能化国家地方联合工程实验室
  • 出版日期:2018-11-30 发布日期:2018-11-30
  • 基金资助:
    国家社会科学基金资助项目(16CGL018);中央高校基本科研业务费专项资金资助项目(2682016CX054);浙江省自然科学基金资助项目(LQ17G030007)。

Service composition in customized pickup point under demand heterogeneity

  • Online:2018-11-30 Published:2018-11-30
  • Supported by:
    Project supported by the National Social Science Foundation,China(No.16CGL018),the Fundamental Research Funds for the Central Universities,China(No.2682016CX054),and the Zhejiang Provincial Natural Science Foundation,China(No.LQ17G030007).

摘要: 为适应顾客需求多元化的趋势,提高自提服务效率,研究了定制化服务理念下的自提点服务产品组合优化问题。应用客户关系生命周期理论进行需求预测,通过顾客权重和效用函数刻画了顾客需求异质性,通过固定成本和变动成本衡量企业的资金投入。建立多目标优化模型,解决了自提服务模式由标准化服务转向定制化服务过程中,在顾客满意度和企业成本之间取得适度平衡的问题,设计NSGA-Ⅱ求解并进行了算法对比。通过算例验证了模型和算法的有效性,揭示了自提点建设运营总成本随顾客总效用的增加而增加;建设运营具有多品种核心服务产品的自提点,辅之以支持性服务产品,将有效提高顾客的效用;企业在决策过程中应具有前瞻性,适当提高自提点处理能力,应对未来需求量的增加。

关键词: 自提点, 需求异质性, 定制化, 服务组合, NSGA-Ⅱ

Abstract: To meet diverse requirements of customer and improve efficiency of pickup service,the pickup service composition under the concept of customized services was studied.The demand was forecasted with customer relationship life cycle theory;the customer demand heterogeneity was depicted by customer weights and utility function;the capital investment in the process of construction and operation was measured by fixed costs and variable costs.Multi-objective optimization model was set up to get moderate balance between customer satisfaction and enterprise cost in the process of pickup service transformed from standard service to customized service.Non-dominated Sorting Genetic Algorithm-Ⅱ (NSGA-Ⅱ) was used to solve the optimization problem,and an example was given to verify the validity of model and algorithm.The results showed that the total cost increased with the growth of total utility;constructing and operating pickup points with various core service products and supportive service products would improve customer utility effectively;capability should be improved properly to meet increasing demand.

Key words: pickup point, demand heterogeneity, customization, service composition, non-dominated sorting genetic algorithm-Ⅱ

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