<p>We study the tactical time slot management problem under mixed logit demand for attended home delivery in subscription settings. We propose a static mixed-integer linear programming model that integrates delivery slot assortment, price discount decisions, and routing optimization while capturing customer heterogeneity through the mixed logit model. To overcome the computational challenges posed by simulation-based choice probabilities, we develop a simulation-based Adaptive Large Neighborhood Search method aligned with a Sample Average Approximation reformulation. Computational experiments on large-scale instances demonstrate the effectiveness of our approach in capturing stochastic customer behavior and preference heterogeneity, providing a scalable and flexible method for optimizing time slot management under complex demand structures.</p>

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A tactical time slot management problem under mixed logit demand

  • Dorsa Abdolhamidi,
  • Virginie Lurkin

摘要

We study the tactical time slot management problem under mixed logit demand for attended home delivery in subscription settings. We propose a static mixed-integer linear programming model that integrates delivery slot assortment, price discount decisions, and routing optimization while capturing customer heterogeneity through the mixed logit model. To overcome the computational challenges posed by simulation-based choice probabilities, we develop a simulation-based Adaptive Large Neighborhood Search method aligned with a Sample Average Approximation reformulation. Computational experiments on large-scale instances demonstrate the effectiveness of our approach in capturing stochastic customer behavior and preference heterogeneity, providing a scalable and flexible method for optimizing time slot management under complex demand structures.