Facing an Arbitrage Opportunity: Trade or Wait?

In traditional thinking, an arbitrageur will trade immediately once an arbitrage opportunity appears. Is this the best strategy for the arbitrageur or it is even better to wait for the best time to trade so as to achieve the maximum pro fit? To answer this question, this paper studies the optimal trading strategies of an arbitrageur … Read more

Certificates of Optimality and Sensitivity Analysis using Generalized Subadditive Generator Functions: A test study on Knapsack Problems

We introduce a family of subadditive functions called Generator Functions for mixed integer linear programs. These functions were previously defined for pure integer programs with non-negative entries by Klabjan [13]. They are feasible in the subadditive dual and we show that they are enough to achieve strong duality. Several properties of the functions are shown. … Read more

On the polyhedrality of cross and quadrilateral closures

Split cuts form a well-known class of valid inequalities for mixed-integer programming problems. Cook, Kannan and Schrijver (1990) showed that the split closure of a rational polyhedron $P$ is again a polyhedron. In this paper, we extend this result from a single rational polyhedron to the union of a finite number of rational polyhedra. We … Read more

A Versatile Heuristic Approach for Generalized Hub Location Problems

The usability of hub location models heavily depends on an appropriate modelling approach for the economies of scale. Realistic hub location models require more sophisticated transport cost structures than the traditional flow-independent discount. We develop a general modelling scheme for such problems allowing the definition of complicated (non-linear) costs and constraints; its structure allows an … Read more

A Characterization of the Lagrange-Karush-Kuhn-Tucker Property

In this note, we revisit the classical first order necessary condition in mathematical programming in infinite dimension. We show that existence of Lagrange-Karush-Kuhn-Tucker multipliers is equivalent to the existence of an error bound for the constraint set, and is also equivalent to a generalized Abadie’s qualification condition. These results extend widely previous one like by … Read more

Steiner Trees with Degree Constraints: Structural Results and an Exact Solution Approach

In this paper we study the Steiner tree problem with degree constraints. Motivated by an application in computational biology we first focus on binary Steiner trees in which all node degrees are required to be at most three. We then present results for general degree-constrained Steiner trees. It is shown that finding a binary Steiner … Read more

Fast Bundle-Level Type Methods for unconstrained and ball-constrained convex optimization

It has been shown in \cite{Lan13-1} that the accelerated prox-level (APL) method and its variant, the uniform smoothing level (USL) method, have optimal iteration complexity for solving black-box and structured convex programming problems without requiring the input of any smoothness information. However, these algorithms require the assumption on the boundedness of the feasible set and … Read more

New Exact Solution Approaches for the Split Delivery Vehicle Routing Problem

In this study, we propose exact solution methods for the Split Delivery Vehicle Routing Problem (SDVRP). We first give a new vehicle-indexed flow formulation for the problem, and then, a relaxation obtained by aggregating the vehicle-indexed variables over all vehicles. This relaxation may have optimal solutions where several vehicles exchange loads at some customers. We … Read more

Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization

In this paper we study stochastic quasi-Newton methods for nonconvex stochastic optimization, where we assume that only stochastic information of the gradients of the objective function is available via a stochastic first-order oracle (SFO). Firstly, we propose a general framework of stochastic quasi-Newton methods for solving nonconvex stochastic optimization. The proposed framework extends the classic … Read more

Use of a Biobjective Direct Search Algorithm in the Process Design of Material Science Applications

This work describes the application of a direct search method to the optimization of problems of real industrial interest, namely three new material science applications designed with the FactSage software. The search method is BiMADS, the biobjective version of the mesh adaptive direct search (MADS) algorithm, designed for blackbox optimization. We give a general description … Read more