Applications – Science and Engineering

Equivalence-Based Reduction and Incremental Optimization for Categorical and Ordinal Classification

Published: 2026/10/03

Data Science Algorithms, Data-Mining, Optimization in Data Science

Exact mathematical programming formulations for estimating classification rules provide guarantees of empirical optimality, but their size grows rapidly with the number of predictive features and model complexity. This paper shows that interpretable classifiers can be estimated by directly maximizing empirical classification accuracy under complexity constraints, using truncation and warm-start strategies compatible with disjunctive normal form … Read more

Differentiating Through Moving Recourse: Feasible Policy Optimization and Finite-Sample Certification for Multistage Stochastic Programs

Published: 2026/09/27

Dynamic Programming, Energy, Stochastic Programming differentiable projection, information relaxation, moving recourse, multistage stochastic programming, optimality gap certification, pathwise gradient, policy optimization, reservoir management

Multistage stochastic programs model decisions under uncertainty where earlier decisions change later feasible sets. We propose a feasible pathwise gradient method (FeasPG) that can update the policy as new sample paths arrive. The policy proposes a decision and projects it onto the current feasible set, so every decision is feasible. We derive the full trajectory … Read more

Two-stage approach for the predispatch problem with uncertain demand using splitting variables in interior-point methods

Published: 2026/09/16

Applications - Science and Engineering, Quadratic Programming, Stochastic Programming interior point methods, optimal power flow, Splitting Variables., stochastic optimization

The stochastic predispatch optimal power flow problem aims to minimize generation costs and transmission losses subject to network constraints under demand uncertainty. We formulate it as a two-stage stochastic quadratic optimization problem with fixed recourse, in which hydroelectric generation constitutes the here-and-now decision, while thermal generation and transmission flows are recourse decisions. Using a splitting-variable … Read more

Two-Stage Stochastic Optimization for Capacitated Facility Location Under Demand Uncertainty

Published: 2026/09/14

Sofiat Ajide

(Mixed) Integer Linear Programming, Facility Planning and Design, Stochastic Programming facility location, optimization under uncertainty, sensitivity analysis, stochastic programming, Two-Stage Recourse, Value of the Stochastic Solution

Facility location decisions are typically made before demand is fully known, yet most applied studies solve a single deterministic model using expected or nominal demand. This paper formulates and solves a capacitated facility location problem using a real academic benchmark instance, then extends it to a two-stage stochastic program in which facility-opening decisions are made … Read more

Twist Without Tangle: Flutter Suppression of Thin-Walled Wing-Engine Systems via Curvilinear Fiber Path Tailoring and Cross-Section Optimization

Published: 2026/09/12

Nima Kakhsaz Malayeri

Applications - Science and Engineering, Optimization of Simulated Systems, Optimization of Systems modeled by PDEs Curvilinear Fiber Path Tailoring, Flutter Optimization, Self-intersection Barrier, shape optimization

Flutter is traditionally delayed by modifying either a structure’s geometry or its stiffness distribution. Here, we show that allowing both to evolve simultaneously can unlock a fundamentally different route to aeroelastic stability. We concurrently optimize the cross-sectional geometry and fiber paths of a composite thin-walled wing–engine system to maximize flutter onset. The wing structure is … Read more

Rooting Out Self-Intersection: An Algebraic Shape-Optimization Barrier

Published: 2026/09/06, Updated: 2026/09/25

Nima Kakhsaz Malayeri

Applications - Science and Engineering, Multidisciplinary Design Optimization, Nonlinear Optimization barrier penalty function, iterative linear algebra techniques, shape optimization, unconstrained minimization

Self-intersection is a fundamental feasibility constraint in shape optimization: a self-crossing boundary leaves its interior, normal field, and finite-element mesh ill-defined, yet most existing barriers rely on heuristic geometric-proximity measures rather than certifying self-intersection directly. We propose a self-intersection barrier grounded in algebraic detection. We derived two bivariate polynomials from a curve’s Fourier coefficients whose … Read more

An optimal orbit design for LISA

Published: 2026/09/03

Yaguang Yang

Constrained Nonlinear Optimization, Multidisciplinary Design Optimization, Optimization of Systems modeled by PDEs constrained nonlinear optimization, formation fly, optimal orbit design

The ESA/NASA joint LISA (laser interferometer space antenna) mission is designed to detect gravitational waves to perform gravitational astronomy. A key mission requirement is the maintenance of a three-spacecraft constellation in a near-equilateral triangular configuration with a prescribed inter-spacecraft separation. Existing approaches have addressed this problem using simplified dynamical models to enhance tractability; however, the … Read more

On the Equivalence of Monge and Kantarovich Problems in Discrete Optimal Transport

Published: 2026/09/01

Thirumulanathan Dhayaparan

Convex and Nonsmooth Optimization, Linear, Cone and Semidefinite Programming, Optimization of Systems modeled by PDEs

Consider a discrete optimal transport problem that has at least two consumers. We show that the Monge and Kantorovich versions of such a discrete optimal transport problem are equivalent for all cost functions if and only if the supply from all the suppliers are equal, and the demand from every consumer is an integral multiple … Read more

Combining Reinforcement Learning with Arc-search Interior-Point Method for Path Planning

Published: 2026/08/21

Yaguang Yang

Constrained Nonlinear Optimization, Control Applications, Nonlinear Optimization arc-search, nonlinear optimization, obstacle avoidance, Path planning

Path planning in environments containing obstacles has numerous practical applications. The problem is challenging because it is inherently nonlinear and nonconvex. Consequently, a variety of techniques have been developed to address this problem, among which machine learning and optimal control (or optimization) have emerged as two prominent approaches. In general, machine learning methods do not … Read more

A Decision-Support Framework for Structuring and Reducing Large Multi-Objective Solution Sets via Clustering: An Application to Proton Therapy

Published: 2026/08/17

Nicole Cristina Cassimiro

(Mixed) Integer Linear Programming, Biomedical Applications, Multi-Criteria Optimization clustering, decision support, extended goal programming, goal programming, intensity modulated proton therapy, multi-criteria decision analysis, multi-objective optimization, multiobjective optimization, OR for medicine, Pareto set reduction, radiotherapy treatment planning, representative selection.

This paper proposes a four-stage decision-support framework for structuring and reducing large multi-objective solution sets into compact and interpretable collections of representative alternatives. The methodology combines: (Phase 1) systematic solution generation through extended goal programming and structured preference exploration; (Phase 2) robustness-aware enrichment and profiling under weight sensitivity analysis; (Phase 3) filtering and dominance-based reduction … Read more