Distributionally Robust Reward-risk Ratio Programming with Wasserstein Metric

Reward-risk ratio (RR) is a very important stock market definition. In recent years, people extend RR model as distributionally robust reward-risk ratio (DRR) to capture the situation that the investor does not have complete information on the distribution of the underlying uncertainty. In this paper, we study the DRR model where the ambiguity on the … Read more

An approximation algorithm for the partial covering 0-1 integer program

The partial covering 0-1 integer program (PCIP) is a relaxed problem of the covering 0-1 integer program (CIP) such that some fixed number of constraints may not be satisfied. This type of relaxation is also discussed in the partial set multi-cover problem (PSMCP) and the partial set cover problem (PSCP). In this paper, we propose … Read more

Optimal Price Zones of Electricity Markets: A Mixed-Integer Multilevel Model and Global Solution Approaches

Mathematical modeling of market design issues in liberalized electricity markets often leads to mixed-integer nonlinear multilevel optimization problems for which no general-purpose solvers exist and which are intractable in general. In this work, we consider the problem of splitting a market area into a given number of price zones such that the resulting market design … Read more

The Robust Uncapacitated Lot Sizing Model with Uncertainty Range

We study robust versions of the uncapacitated lot sizing problem, where the demand is subject to uncertainty. The robust models are guided by three parameters, namely, the total scaled uncertainty budget, the minimum number of periods in which one would like the demand to be protected against uncertainty, and the minimum scaled protection level per … Read more

Geometric descent method for convex composite minimization

In this paper, we extend the geometric descent method recently proposed by Bubeck, Lee and Singh to tackle nonsmooth and strongly convex composite problems. We prove that our proposed algorithm, dubbed geometric proximal gradient method (GeoPG), converges with a linear rate $(1-1/\sqrt{\kappa})$ and thus achieves the optimal rate among first-order methods, where $\kappa$ is the … Read more

Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization

A method is proposed for solving equality constrained nonlinear optimization problems involving twice continuously differentiable functions. The method employs a trust funnel approach consisting of two phases: a first phase to locate an $\epsilon$-feasible point and a second phase to seek optimality while maintaining at least $\epsilon$-feasibility. A two-phase approach of this kind based on … Read more

Fooling Sets and the Spanning Tree Polytope

In the study of extensions of polytopes of combinatorial optimization problems, a notorious open question is that for the size of the smallest extended formulation of the Minimum Spanning Tree problem on a complete graph with n nodes. The best known lower bound is \Omega(n^2), the best known upper bound is O(n^3). In this note … Read more

The Selective Traveling Salesman Problem with Draught Limits

This paper introduces the Selective Traveling Salesman Problem with Draught Limits, an extension of Traveling Salesman Problem with Draught Limits, wherein the goal is to design maximal profit tour respecting draught limit constraints of the visited ports. We propose a mixed integer linear programming formulation for this problem. The proposed mixed integer program is used … Read more

An optimization-based approach for delivering radio-pharmaceuticals to medical imaging centers

It is widely recognized that early diagnosis of most types of cancers can increase the chances of full recovery or substantially prolong the life of patients. Positron Emission Tomography (PET) has become the standard way to diagnose many types of cancers by generating high quality images of the affected organs. In order to create an … Read more