Meta Heuristics

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

    Discovering Heuristics with Large Language Models (LLMs) for Mixed-Integer Programs: Single-Machine Scheduling

  • I. Esra Buyuktahtakin Toy
    • Categories (Mixed) Integer Linear Programming, Combinatorial Optimization, Meta Heuristics Tags , , , , , , ,

    TitleDiscovering Heuristics with Large Language Models (LLMs) for Mixed-Integer Programs: Single-Machine Scheduling Authorsİbrahim Oğuz Çetinkaya^1; İ. Esra Büyüktahtakın^1*; Parshin Shojaee^2; Chandan K. Reddy^2 Affiliations^1 Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, USA^2 Department of Computer Science, Virginia Tech, Arlington, VA, USA Abstract: Our study contributes to the scheduling and combinatorial optimization … 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

    A Traveling Salesman Problem with Drone Stations and Speed-Optimized Drones

  • Chun Cheng
    • Categories Meta Heuristics, Transportation Tags

    With e-commerce expanding rapidly, last-mile delivery challenges have been exacerbated, necessitating innovative logistics to reduce operational costs and improve delivery speed. This paper investigates a traveling salesman problem with drone stations, where a truck collaborates with multiple drones docked at candidate drone stations to serve customers. In contrast to existing studies that typically assume fixed … Read more

    A 2-index Stage-based Formulation and a Construct-Merge-Solve & Adapt Algorithm for the Flying Sidekick Traveling Salesman Problem

  • Tran Khanh
    • Categories (Mixed) Integer Linear Programming, Combinatorial Optimization, Meta Heuristics

    In this work, we present the first 2-index stage-based formulation for the Flying Sidekick Traveling Salesman Problem (FSTSP). Additionally, we propose a Construct-Merge-Solve & Adapt (CMSA) algorithm designed to generate high-quality feasible solutions. Experimental results demonstrate that the proposed algorithm consistently produces good solutions in a fraction of the time required by state-of-the-art mixed-integer linear … Read more

    Hybrid iterated local search algorithm for the vehicle routing problem with lockers

  • Bruno Oliveira
  • Artur Alves Pessoa
  • Marcos Roboredo
    • Categories Combinatorial Optimization, Integer Programming, Meta Heuristics Tags , , ,

    In the Vehicle Routing Problem (VRP) with Lockers, the vertices in a graph are divided into two key subsets: a customer set and a locker set, with lockers serving as alternative delivery points for the customer’s parcel. This paper presents a generic VRP with lockers, where a customer’s parcel can be delivered either to its … Read more

    Equity-Driven Workload Allocation for Crowdsourced Last-Mile Delivery

  • Abhay Sobhanan
  • Hadi Charkhgard
  • Iman Dayarian
    • Categories Meta Heuristics, Multi-Criteria Optimization, Transportation Tags , , , ,

    Crowdshipping, a rapidly growing approach in Last-Mile Delivery (LMD), relies on independent crowdworkers for delivery orders. Building a sustainable network of crowdshippers is essential for the survival and growth of such systems, while their participation is primarily motivated by fair pay. Additionally, the financial well-being of crowdworkers is sensitive to fair compensation, especially for those … Read more

    Adjustable robust optimization for fleet sizing problem in closed-loop supply chains with simultaneous delivery and pickup

  • Ali Borumand
  • Ali Nookabadi
    • Categories (Mixed) Integer Linear Programming, Meta Heuristics, Robust Optimization Tags , , , ,

    The Fleet Sizing Problem (FSP) stands as a critical challenge within the realm of logistics and supply chain management, particularly in the context of Closed-Loop Supply Chains (CLSC). The significance of addressing the FSP lies in its direct impact on operational costs, resource utilization, and environmental sustainability. By effectively optimizing fleet size, organizations can streamline … Read more

    Optimization Over Trained Neural Networks: Taking a Relaxing Walk

  • Jiatai Tong
  • Junyang Cai
  • Thiago Serra
    • Categories (Mixed) Integer Linear Programming, Data-Mining, Meta Heuristics

    Besides training, mathematical optimization is also used in deep learning to model and solve formulations over trained neural networks for purposes such as verification, compression, and optimization with learned constraints. However, solving these formulations soon becomes difficult as the network size grows due to the weak linear relaxation and dense constraint matrix. We have seen … Read more

    Exact Solutions for the NP-hard Wasserstein Barycenter Problem using a Doubly Nonnegative Relaxation and a Splitting Method

  • Woosuk L. Jung
  • Walaa M. Moursi
  • Henry Wolkowicz
    • Categories Combinatorial Optimization, Meta Heuristics, Semi-definite Programming

    The simplified Wasserstein barycenter problem, also known as the cheapest hub problem, consists in selecting one point from each of \(k\) given sets, each set consisting of \(n\) points, with the aim of minimizing the sum of distances to the barycenter of the \(k\) chosen points. This problem is also known as the cheapest hub … Read more