Xin Chen

Optimality Gap of Tailored Base-Surge Policies Decays Exponentially in Regular-Source Lead Times for Dual-Sourcing Models

  • Xin Chen
  • Shuai Li
  • Weijun Xie
    • Categories Dynamic Programming, Stochastic Programming, Supply Chain Management Tags , , , , ,

    This paper resolves an open problem posed in the literature by proving that, in dual-sourcing inventory systems, the optimality gap of tailored base-surge (TBS) policies decays exponentially with the regular source lead time, with the express-source lead time fixed. In contrast to the existing approach, which relies on conditional Jensen inequalities and a vanishing-discount argument … Read more

    Isotonic Optimization with Fixed Costs

  • Xin Chen
  • Shuai Li
  • Weijun Xie
    • Categories (Mixed) Integer Nonlinear Programming, Dynamic Programming, Supply Chain Management Tags , , ,

    This paper introduces a generalized isotonic optimization framework over an arborescence graph, where each node incurs state-dependent convex costs and a fixed cost upon strict increases. We begin with the special case in which the arborescence is a path and develop a dynamic programming (DP) algorithm with an initial complexity of $O(n^3)$, which we improve … Read more

    A Tractable Approximation of Stochastic Programming via Robust Optimization

  • Xin Chen
  • Peng Sun
  • Jiawei Zhang
  • Melvyn Sim
    • Categories Robust Optimization, Second-Order Cone Programming, Stochastic Programming Tags , , ,

    Stochastic programming, despite its immense modeling capabilities, is well known to be computationally excruciating. In this paper, we introduce a unified framework of approximating multiperiod stochastic programming from the perspective of robust optimization. Specifically, we propose a framework that integrates multistage modeling with safeguarding constraints. The framework is computationally tractable in the form of second … Read more

    A Robust Optimization Perspective of Stochastic Programming

  • Xin Chen
  • Peng Sun
  • Melvyn Sim
    • Categories Robust Optimization, Stochastic Programming Tags , ,

    In this paper, we introduce an approach for constructing uncertainty sets for robust optimization using new deviation measures for bounded random variables known as the forward and backward deviations. These deviation measures capture distributional asymmetry and lead to better approximations of chance constraints. We also propose a tractable robust optimization approach for obtaining robust solutions … Read more