Extended Formulations and Branch-and-Cut Algorithms for the Black-and-White Traveling Salesman Problem

In this paper we study integer linear programming models and develop branch-and-cut algorithms to solve the Black-and-White Traveling Salesman Problem (BWTSP) (Bourgeois et al., 2003) which is a variant of the well known Traveling Salesman Problem (TSP). Two strategies to model the BWTSP have been used in the literature. The problem is either modeled on … Read more

Data-Driven Risk-Averse Stochastic Program And Renewable Energy Integration

With increasing penetration of renewable energy into the power grid and its intermittent nature, it is crucial and challenging for system operators to provide reliable and cost effective daily electricity generation scheduling. In this dissertation, we present our recently developed innovative modeling and solution approaches to address this challenging problem. We start with developing several … Read more

Decomposition-Based Approximation Algorithms for the One-Warehouse Multi-Retailer Problem with Concave Batch Order Costs

We study the one-warehouse multi-retailer (OWMR) problem under deterministic dynamic demand and concave batch order costs, where order batches have an identical capacity and the order cost function for each facility is concave within the batch. Under appropriate assumptions on holding cost structure, we obtain lower bounds via a decomposition that splits the two-echelon problem … Read more

Formulations and Decomposition Methods for the Incomplete Hub Location Problem With and Without Hop-Constraints

The incomplete hub location problem with and without hop-constraints is modeled using a Leontief substitution system approach. The Leontief formalism provides a set of important theoretical properties and delivers formulations with tight linear bounds that can explicitly incorporate hop constraints for each origin-destination pair of demands. Furthermore, the proposed formulations are amenable to a Benders … Read more

Improving Benders decomposition via a non-linear cut selection procedure

A non-linear lifting procedure is proposed to generate high density Benders cuts. The new denser cuts cover more master problem variables than traditional Benders cuts, shortening the required number of iterations to reach optimality, and speeding up the Benders decomposition algorithm. To lessen the intricacy stemmed from the non-linearity, a simple outer approximation lineariza- tion … Read more

Strengthened MILP Formulation for Combined-Cycle Units

Due to the increased utilization of gas-fired combined-cycle units for power generation in the U.S., accurate and computationally efficient models are more and more needed. The recently proposed edge-based formulation for combined-cycle units helps accurately describe the operations of combined-cycle units including capturing the transition processes and physical constraints for each turbine. In this paper, … Read more

Polynomial Time Algorithms and Extended Formulations for Unit Commitment Problems

Recently increasing penetration of renewable energy generation brings challenges for power system operators to perform efficient power generation daily scheduling, due to the intermittent nature of the renewable generation and discrete decisions of each generation unit. Among all aspects to be considered, unit commitment polytope is fundamental and embedded in the models at different stages … Read more

Creating Standard Load Profiles in Residential and Commercial Sectors in Germany for 2016, 2025 and 2040

Standard load profiles (SLPs) are used to calculate the natural gas demand of non-daily metered customers based on temperature forecasts. The most recent version of natural gas SLPs in Germany was published by the Federal Association of Energy and Water in June 2015. With the concept SigLinDE, a linearization of the old SLPs was carried … Read more

Robust optimization of noisy blackbox problems using the Mesh Adaptive Direct Search algorithm

Blackbox optimization problems are often contaminated with numerical noise, and direct search methods such as the Mesh Adaptive Direct Search (MADS) algorithm may get stuck at solutions artificially created by the noise. We propose a way to smooth out the objective function of an unconstrained problem using previously evaluated function evaluations, rather than resampling points. … Read more

Moulin Mechanism Design for Freight Consolidation

In freight consolidation, a “fair” cost allocation scheme is critical for forming and sustaining horizontal cooperation that leads to reduced transportation cost. We study a cost-sharing problem in a freight consolidation system with one consolidation center and a common destination. In particular, we design a mechanism that collects bids from a set of suppliers, and … Read more