Crew Scheduling and Routing Problem in Road Restoration via Branch-and-Price Algorithms

  • Alfredo Moreno
  • Pedro Munari
  • Douglas Alem
    • Categories Applications - OR and Management Sciences, Transportation Tags , , , ,

    This paper addresses the single crew scheduling and routing problem in the context of road network repair and restoration, which is critical in assisting complex post-disaster decisions in humanitarian logistics settings. We present three novel formulations for this problem, which are the first suitable for column generation and branch-and-price (BP) algorithms. Specifically, our first formulation … Read more

    Integrating Public Transport in Sustainable Last-Mile Delivery: Column Generation Approaches

  • Diego Delle Donne
  • Alberto Santini
  • Claudia Archetti
    • Categories (Mixed) Integer Linear Programming, Combinatorial Optimization, Production and Logistics Tags , , , ,

    We tackle the problem of coordinating a three-echelon last-mile delivery system. In the first echelon, trucks transport parcels from distribution centres outside the city to public transport stops. In the second echelon, the parcels move on public transport and reach the city centre. In the third echelon, zero-emission vehicles pick up the parcels at public … Read more

    An Inexact Restoration Direct Multisearch Filter Approach to Multiobjective Constrained Derivative-free Optimization

  • Everton Silva
  • Ana Luisa Custódio
    • Categories Constrained Nonlinear Optimization, Nonsmooth Optimization Tags , , , , , ,

    Direct Multisearch (DMS) is a well-established class of methods for multiobjective derivative-free optimization, where constraints are addressed by an extreme barrier approach, only evaluating feasible points. In this work, we propose a filter approach, combined with an inexact feasibility restoration step, to address constraints in the DMS framework. The filter approach treats feasibility as an … Read more

    Greedy Newton: Newton’s Method with Exact Line Search

  • Betty Shea
  • Mark Schmidt
    • Categories Convex Optimization

    A defining characteristic of Newton’s method is local superlinear convergence within a neighbourhood of a strict local minimum. However, outside this neighborhood Newton’s method can converge slowly or even diverge. A common approach to dealing with non-convergence is using a step size that is set by an Armijo backtracking line search. With suitable initialization the … Read more

    Solving separable convex optimization problems: Faster prediction-correction framework

  • Tao Zhang
    • Categories Convex and Nonsmooth Optimization, Convex Optimization, Nonsmooth Optimization

    He and Yuan’s prediction-correction framework [SIAM J. Numer. Anal. 50: 700-709, 2012] is able to provide convergent algorithms for solving separable convex optimization problems at a rate of $O(1/t)$ ($t$ represents iteration times) in both ergodic (the average of iteration) and pointwise senses. This paper presents a faster prediction-correction framework at a rate of $O(1/t)$ … Read more

    Information Basis in Dynamic Robust Optimization

  • Ningji Wei
  • Peter Yun Zhang
    • Categories Robust Optimization Tags , , ,

    Dynamic robust optimization deals with sequential, multi-stage decisions in the face of uncertain, worst-case scenarios. To manage its complexity and the curse of dimensionality, decision rules simplify the search for an optimal policy. This paper explores a middle ground between two common decision rules: simple but imprecise constant policies, and accurate but less scalable affine … Read more

    Alternate Training of Shared and Task-Specific Parameters for Multi-Task Neural Networks

  • Stefania Bellavia
    • Categories Nonlinear Optimization, Stochastic Programming Tags , ,

    This paper introduces novel alternate training procedures for hard-parameter sharing Multi-Task Neural Networks (MTNNs). Traditional MTNN training faces challenges in managing conflicting loss gradients, often yielding sub-optimal performance. The proposed alternate training method updates shared and task-specific weights alternately, exploiting the multi-head architecture of the model. This approach reduces computational costs, enhances training regularization, and … Read more

    A semi-smooth Newton method for general projection equations applied to the nearest correlation matrix problem

  • Nicolas F. Armijo
  • Yunier Bello-Cruz
  • Gabriel Haeser
    • Categories Semi-definite Programming Tags , , ,

    In this paper, we extend and investigate the properties of the semi-smooth Newton method when applied to a general projection equation in finite dimensional spaces. We first present results concerning Clarke’s generalized Jacobian of the projection onto a closed and convex cone. We then describe the iterative process for the general cone case and establish … Read more

    Strong global convergence properties of algorithms for nonlinear symmetric cone programming

  • Roberto Andreani
  • Gabriel Haeser
  • Alberto Ramos
  • Daiana O. Santos
  • Leonardo D. Secchin
  • Ariel Serranoni
    • Categories Cone Programming, Second-Order Cone Programming, Semi-definite Programming Tags , , ,

    Sequential optimality conditions have played a major role in proving strong global convergence properties of numerical algorithms for many classes of optimization problems. In particular, the way complementarity is dealt is fundamental to achieve a strong condition. Typically, one uses the inner product structure to measure complementarity, which gives a very general approach to a … Read more

    A relaxed quasinormality condition and the boundedness of dual augmented Lagrangian sequences

  • Roberto Andreani
  • Gabriel Haeser
  • María Laura Schuverdt
  • Leonardo D. Secchin
    • Categories Nonlinear Optimization Tags , , ,

    Global convergence of augmented Lagrangian methods to a first-order stationary point is well-known to hold under considerably weak constraint qualifications. In particular, several constant rank-type conditions have been introduced for this purpose which turned out to be relevant also beyond this scope. In this paper we show that in fact under these conditions subsequences of … Read more