Polynomial-Time Algorithms for Setting Tight Big-M Coefficients in Transmission Expansion Planning with Disconnected Buses

The increasing penetration of renewable energy into power systems necessitates the development of effective methodologies to integrate initially disconnected generation sources into the grid. This paper introduces the Longest Shortest-Path-Connection (LSPC) algorithm, a graph-based method to enhance the mixed-integer linear programming disjunctive formulation of Transmission Expansion Planning (TEP) using valid inequalities (VIs). Traditional approaches for … Read more

Neural Embedded Mixed-Integer Optimization for Location-Routing Problems

We present a novel framework that combines machine learning with mixed-integer optimization to solve the Capacitated Location-Routing Problem (CLRP). The CLRP is a classical yet NP-hard problem that integrates strategic facility location with operational vehicle routing decisions, aiming to simultaneously minimize both fixed and variable costs. The proposed method first trains a permutationally invariant neural … Read more

Reduced Sample Complexity in Scenario-Based Control System Design via Constraint Scaling

The scenario approach is widely used in robust control system design and chance-constrained optimization, maintaining convexity without requiring assumptions about the probability distribution of uncertain parameters. However, the approach can demand large sample sizes, making it intractable for safety-critical applications that require very low levels of constraint violation. To address this challenge, we propose a … Read more

A Jamming Game for Fleets of Mobile Vehicles

We consider a two-player Nash game in which each player represents a fleet of unmanned aerial vehicles. Each fleet is supposed to distribute information among fleet members, while simultaneously trying to prevent the opposite fleet from achieving this. Using the electro-magnetic spectrum’s properties, we model each fleet’s task as a nonlinear Nash game. By reformulating … Read more

A Dynamic Strategic Plan for the Transition to a Clean Bus Fleet using Multi-Stage Stochastic Programming with a Case Study in Istanbul

In recent years, the transition to clean bus fleets has accelerated. Although this transition might bring environmental and economic benefits, it requires a long-term strategic plan due to the large investment costs involved. This paper proposes a multi-stage stochastic program to optimize strategic plans for the clean bus fleet transition that explicitly considers the uncertainty … Read more

Estimating the Unobservable Components of Electricity Demand Response with Inverse Optimization

Understanding and predicting the electricity demand responses to prices are critical activities for system operators, retailers, and regulators. While conventional machine learning and time series analyses have been adequate for the routine demand patterns that have adapted only slowly over many years, the emergence of active consumers with flexible assets such as solar-plus-storage systems, and … Read more

A homotopy for the reliable estimation of model parameters in chromatography processes

Mathematical modeling, simulation, and optimization can significantly support the development and characterization of chromatography steps in the biopharmaceutical industry. Particularly mechanistic models become preferably used, as these models, once carefully calibrated, can be employed for a reliable optimization. However, model calibration is a difficult task in this context due to high correlations between parameters, highly … Read more

Optimizing the lead time of operational flexibility trading from distributed industrial energy systems in future energy and flexibility markets

To meet the challenges of increasing volatile and distributed renewable energy generation in the electric grid, local flexibility and energy markets are currently investigated. These markets aim to encourage prosumers to trade their available flexible power locally, to be used if a grid congestion is being predicted. The markets are emerging, but the characterizing parameter … Read more

Global Optimization of Non-Linear Systems of Equations by Simulating the Flight of a Projectile in the Conformational Space

A new heuristic optimization algorithm is presented based on an analogy with the physical phenomenon of a projectile launched in a conformational space under the influence of a gravitational force. Its implementation simplicity and the option to enhance it with local search methods make it ideal for the optimization of non-linear systems of equations. The … Read more

Immunity to Increasing Condition Numbers of Linear Superiorization versus Linear Programming

Given a family of linear constraints and a linear objective function one can consider whether to apply a Linear Programming (LP) algorithm or use a Linear Superiorization (LinSup) algorithm on this data. In the LP methodology one aims at finding a point that fulfills the constraints and has the minimal value of the objective function … Read more