On Intersection of Two Mixing Sets with Applications to Joint Chance-Constrained Programs

We study the polyhedral structure of a generalization of a mixing set described by the intersection of two mixing sets with two shared continuous variables, where one continuous variable has a positive coefficient in one mixing set, and a negative coefficient in the other. Our developments are motivated from a key substructure of linear joint … Read more

The Multiple Part Type Cyclic Flow Shop Robotic Cell Scheduling Problem: A Novel and Comprehensive Mixed Integer Linear Programming Approach

This paper considers the problem of cyclic ow shop robotic cell scheduling deploying several single and dual gripper robots. In this problem, dierent part types are successively processed on multiple machines with dierent pickup criteria including free pickup, pickup within time-windows and no-waiting times. The parts are transported between the machines by the robots. We … Read more

Multiechelon Lot Sizing: New Complexities and Inequalities

We study a multiechelon supply chain model that consists of a production level and several transportation levels, where the demands can exist in the production echelon as well as any transportation echelons. With the presence of stationary production capacity and general cost functions, our model integrates production, inventory and transportation decisions and generalizes existing literature … Read more

Reliable single allocation hub location problem under hub breakdowns

The design of hub-and-spoke transport networks is a strategic planning problem, as the choice of hub locations has to remain unchanged for long time periods. However, strikes, disasters or traffic breakdown can lead to the unavailability of a hub for a short period of time. Therefore it is important to consider such events already in … Read more

Risk-based Loan Pricing: Portfolio Optimization Approach With Marginal Risk Contribution

We consider a lender (bank) who determines the optimal loan price (interest rates) to offer to prospective borrowers under uncertain risk and borrowers’ response. A borrower may or may not accept the loan at the price offered, and in the presence of default risk, both the principal loaned and the interest income become uncertain. We … 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

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

Recent Progress Using Matheuristics for Strategic Maritime Inventory Routing

This paper presents an extensive computational study of simple, but prominent matheuristics (i.e., heuristics that rely on mathematical programming models) to fi nd high quality ship schedules and inventory policies for a class of maritime inventory routing problems. Our computational experiments are performed on a set of the publicly available MIRPLib instances. This class of inventory … 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