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Data-Driven Optimization for Meal Delivery: A Reinforcement Learning Approach for Order-Courier Assignment and Routing at Meituan

  • Ramon Auad
  • Felipe Lagos
  • Tomas Lagos
    • Categories Dynamic Programming, Meta Heuristics, Transportation Tags

    The rapid growth of online meal delivery has introduced complex logistical challenges, where platforms must dynamically assign orders to couriers while accounting for demand uncertainty, courier autonomy, and service efficiency. Traditional dispatching methods, often focused on short-term cost minimization, fail to capture the long-term implications of assignment decisions on system-wide performance. This paper presents a … Read more

    blockSQP 2: exploiting structure to improve performance

  • Reinhold Wittmann
  • Sebastian Sager
    • Categories Dynamic Programming, Nonlinear Optimization Tags , , , ,

    Abstract One approach to solving optimal control problems is Bock’s direct multiple shoot- ing method. This method yields lifted nonlinear optimization problems (NLPs) with a spe- cific block structure. Exploiting this structure via tailored optimization algorithms can be computationally beneficial. We propose such methods, primarily within the framework of fil- ter line search sequential quadratic … Read more

    Global Multi-Objective Simulation Optimization: Error Bounds and Convergence Rates

  • Burla E. Ondes
  • Susan R. Hunter
    • Categories Global Optimization, Multi-Criteria Optimization, Optimization of Simulated Systems Tags , , , ,

    Consider the context of solving a multi-objective simulation optimization problem with one or more continuous objective functions to global optimality on a compact feasible set. For a simple algorithm that consists of selecting a finite set of feasible points using a space-filling design, expending the same number of simulation replications at each point to estimate … Read more

    A linearly convergent algorithm for variational inequalities based on fiber bundle

  • Hongbo Sun
    • Categories Complementarity and Variational Inequalities, Game Theory Tags , , ,

    The variational inequality (VI) problem is a fundamental mathematical framework for many classical problems. This paper introduces an algorithm that applies to arbitrary finite-dimensional VIs with general compact convex sets and general continuous functions. The algorithm guarantees global linear convergence to an approximate solution without requiring any assumptions, including the typical monotonicity. Our approach adapts … Read more

    A Multivariate Loss Ratio Approach for Systemic Risk Measurement and Allocation

  • Wei Wang
  • HuifuXu
    • Categories Finance and Economics, Multi-Criteria Optimization, Other Topics Tags , , , ,

    The primary challenges in systemic risk measurement involve determining an overall reserve level of risk capital and allocating it to different components based on their systemic relevance. In this paper, we introduce a multivariate loss ratio measure (MLRM), which is the minimum amount of capital to be injected into a financial system such that the … Read more

    Properties of Enclosures in Multiobjective Optimization

  • Gabriele Eichfelder
  • Daniel Hoff
    • Categories Global Optimization, Multi-Criteria Optimization, Nonlinear Optimization Tags , ,

    A widely used approximation concept in multiobjective optimization is the concept of enclosures. These are unions of boxes defined by lower and upper bound sets that are used to cover optimal sets of multiobjective optimization problems in the image space. The width of an enclosure is taken as a quality measure. In this paper, we … Read more

    Consistent and unbiased estimation of the hypervolume of an unknown true Pareto front

  • Xavier Gandibleux
  • Andrzej Jaszkiewicz
    • Categories Combinatorial Optimization, Meta Heuristics, Multi-Criteria Optimization Tags , ,

    Hypervolume is most likely the most often used set quality indicator in (evolutionary) multi-objective optimization. It may be used to compare the quality of solution sets whose images in the objective space are approximations of the true Pareto front. Although in this way we may compare two or more approximations, our knowledge is limited without … 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

    Assessing Green Hydrogen Production via Offshore Wind in the Dutch North Sea: Complementing Techno-Economic Simulation With Machine Learning and Optimization

  • Justin Starreveld
  • Dick den Hertog
  • Kenneth Bruninx
  • Alessandro Bianchini
  • Riccardo Travaglini
  • R.J van 't Veer
  • Laurens Frowijn
    • Categories Applications - OR and Management Sciences, Energy, Optimization of Simulated Systems Tags , , ,

    As countries seek to decarbonize their energy systems, green hydrogen has emerged as a promising energy carrier. This paper studies the production of green hydrogen from offshore wind in the Dutch North Sea, with particular emphasis on understanding how system design decisions and uncertain parameters affect key performance indicators. The analysis builds on a detailed … Read more

    On Subproblem Tradeoffs in Decomposition and Coordination of Multiobjective Optimization Problems

  • Philip de Castro
  • Margaret Wiecek
    • Categories Multi-Criteria Optimization

    Multiobjective optimization is widely used in applications for modeling and solving complex decision-making problems. To help resolve computational and cognitive difficulties associated with problems which have more than three or four objectives, we propose a decomposition and coordination methodology to support decision making for large multiobjective optimization problems (MOPs) with global, quasi-global, and local variables. … Read more