A Stochastic Benders Decomposition Scheme for Large-Scale Data-Driven Network Design

Network design problems involve constructing edges in a transportation or supply chain network to minimize construction and daily operational costs. We study a data-driven version where operational costs are uncertain and estimated on historical data. This problem is computationally challenging, and instances with as few as 50 nodes cannot be solved to optimality by current … Read more

On a Frank-Wolfe Approach for Abs-smooth Functions

We propose an algorithm which appears to be the first bridge between the fields of conditional gradient methods and abs-smooth optimization. Our nonsmooth nonconvex problem setting is motivated by machine learning, since the broad class of abs-smooth functions includes, for instance, the squared $l_2$-error of a neural network with ReLU or hinge loss activation. To … Read more

Effective matrix adaptation strategy for noisy derivative-free optimization

In this paper, we introduce a new effective matrix adaptation evolution strategy (MADFO) for noisy derivative-free optimization problems. Like every MAES solver, MADFO consists of three phases: mutation, selection and recombination. MADFO improves the mutation phase by generating good step sizes, neither too small nor too large, that increase the probability of selecting mutation points … Read more

An approximation algorithm for multi-objective mixed-integer convex optimization

In this article we introduce an algorithm that approximates Pareto fronts of multiobjective mixed-integer convex optimization problems. The algorithm constructs an inner and outer approximation of the front exploiting the convexity of the patches and is applicable to problems with an arbitrary number of criteria. In the algorithm, the problem is decomposed into patches, which … Read more

Stable Set Polytopes with High Lift-and-Project Ranks for the Lovász-Schrijver SDP Operator

\(\) We study the lift-and-project rank of the stable set polytopes of graphs with respect to the Lovász-Schrijver SDP operator \( \text{LS}_+\), with a particular focus on a search for relatively small graphs with high \( \text{LS}_+\)-rank (the least number of iterations of the \( \text{LS}_+\) operator on the fractional stable set polytope to compute … Read more

Column Elimination for Capacitated Vehicle Routing Problems

We introduce a column elimination procedure for the capacitated vehicle routing problem. Our procedure maintains a decision diagram to represent a relaxation of the set of feasible routes, over which we define a constrained network flow. The optimal solution corresponds to a collection of paths in the decision diagram and yields a dual bound. The … Read more

Robust Workforce Management with Crowdsourced Delivery

We investigate how crowdsourced delivery platforms with both contracted and ad-hoc couriers can effectively manage their workforce to meet delivery demands amidst uncertainties. Our objective is to minimize the hiring costs of contracted couriers and the crowdsourcing costs of ad-hoc couriers while considering the uncertain availability and behavior of the latter. Due to the complication … Read more

Evaluation of Political Redistricting in Japan by Optimization and Enumeration

The political/electoral districting problem for the single-seat constituency system is a problem of decomposing a graph into connected components of a given number of seats under several conditions and objectives. We evaluate and analyze the current division of single-seat constituencies for the House of Representatives using optimization and enumeration. The objective function is to minimize … Read more

Multithread Interval Scheduling with Flexible Machine Availabilities: Complexity and Efficient Algorithms

In the known Interval Scheduling problem with Machine Availabilities (ISMA), each machine has a contiguous availability interval and each job has a specic time interval which has to be scheduled. The objective is to schedule all jobs such that the machines’ availability intervals are respected or to decide that there exists no such schedule. We … Read more

A worst-case complexity analysis for Riemannian non-monotone line-search methods

In this paper we deal with non-monotone line-search methods to minimize a smooth cost function on a Riemannian manifold. In particular, we study the number of iterations necessary for this class of algorithms to obtain e-approximated stationary points. Specifically, we prove that under a regularity Lipschitz-type condition on the pullbacks of the cost function to … Read more