Applications – Science and Engineering

A Dynamic Strategic Plan for Transition to Campus-Scale Clean Electricity Using Multi-Stage Stochastic Programming

  • Ahmet Emir Şener
  • Burak Kocuk
  • Tuğçe Yüksel
    • Categories Energy, Stochastic Programming Tags , , ,

    The decarbonization of energy systems at energy-intensive sites is an essential component of global climate mitigation, yet such transitions involve substantial capital requirements, ongoing technological progress, and the operational complexities of renewable integration. This study presents a dynamic strategic planning framework that applies multi-stage stochastic programming to guide clean electricity transitions at the campus level. … Read more

    Two approaches to piecewise affine approximation

  • Nadezda Sukhorukova
    • Categories Applications - OR and Management Sciences, Approximation Algorithms, Data-Mining Tags , , ,

    The problem of approximation by piecewise affine functions has been studied for several decades (least squares and uniform approximation). If the location of switches from one affine piece to another (knots for univariate approximation) is known the problem is convex and there are several approaches to solve this problem. If the location of such switches … Read more

    Algorithmic Approaches for Identifying the Trade-off between Pessimism and Optimism in a Stochastic Fixed Charge Facility Location Problem

  • Man Yiu Tsang
  • Karmel S. Shehadeh
    • Categories Facility Planning and Design, Robust Optimization, Stochastic Programming Tags , , ,

    We introduce new algorithms to identify the trade-off (TRO) between adopting a distributional belief and hedging against ambiguity when modeling uncertainty in a capacitated fixed charge facility location problem (CFLP). We first formulate a TRO model for the CFLP (TRO-CFLP), which determines the number of facilities to open by minimizing the fixed establishment cost and … Read more

    ASMOP: Additional sampling stochastic trust region method for multi-objective problems

  • Nataša Krklec Jerinkić
  • Luka Rutešić
    • Categories Multi-Criteria Optimization, Optimization of Systems modeled by PDEs, Stochastic Programming Tags , , , , ,

    We consider an unconstrained multi-criteria optimization problem with finite sum objective functions. The proposed algorithm belongs to a non-monotone trust-region framework where additional sampling approach is used to govern the sample size and the acceptance of a candidate point. Depending on the problem, the method can result in a mini-batch or an increasing sample size … Read more

    A relax-fix-and-exclude algorithm for an MINLP problem with multilinear interpolations

  • Bruno Machado Pacheco
  • Laio Seman
    • Categories (Mixed) Integer Nonlinear Programming, Chemical Engineering, Global Optimization Applications Tags , ,

    This paper introduces a novel algorithm for Mixed-Integer Nonlinear Programming (MINLP) problems with multilinear interpolations of look-up tables. These problems arise when objectives or constraints contain black-box functions only known at a finite set of evaluations on a predefined grid. We derive a piecewise-linear relaxation for the multilinear interpolants, which require an MINLP formulation. Supported … Read more

    Interpretable SHAP-bounded Bayesian Optimization for Underwater Acoustic Metamaterial Coating Design

  • Elnaz Hajizadeh
    • Categories Civil and Environmental Engineering, Mechanical Engineering Tags , , , ,

    We developed an interpretability informed Bayesian optimization framework to optimize underwater acoustic coatings based on polyurethane elastomers with embedded metamaterial features. A data driven model was employed to analyze the relationship between acoustic performance, specifically sound absorption and the corresponding design variables. By leveraging SHapley Additive exPlanations (SHAP), a machine learning interpretability tool, we identified … Read more

    Constrained Bayesian Accelerated Design of Acoustic Polyurethane Coatings with Metamaterial Features Under Hydrostatic Pressure

  • Elnaz Hajizadeh
    • Categories Civil and Environmental Engineering, Mechanical Engineering Tags , , ,

    Here we propose a novel, fully automated framework for accelerated design of underwater acoustic coatings, targeting the reduction of acoustic signature of naval platforms under operational conditions, by coupling Bayesian Optimization (BO) with a 2-step Finite Element Model (FEM). The developed FEMs evaluate the acoustic performance of polyurethane (PU) coatings with embedded metamaterial features under … Read more

    Data-Driven Multistage Scheduling Optimization for Refinery Production under Uncertainty: Systematic Framework, Modeling Approach, and Application Analysis

  • Biao Han
    • Categories Control Applications, Scheduling, Stochastic Programming Tags , , , , , , ,

    The widespread existence of various uncertainties makes the inherently complex refinery production scheduling problem even more challenging. To address this issue, this paper proposes a viable systematic data-driven multistage scheduling optimization framework and develops a corresponding structured modeling methodology. Under this paradigm, unit-level advanced control and plant-level intelligent scheduling are coordinated to jointly deal with … Read more

    A Framework for Explainable Knowledge Generation with Expensive Sample Evaluations

  • Alberto Costa
    • Categories Global Optimization, Multidisciplinary Design Optimization, Optimization of Simulated Systems Tags , , ,

    Real world problems often require complex modeling and computation efforts to be effectively addressed. Relying solely on data-driven approaches without integrating physics-based models can result in limited predictive capabilities. Even advanced techniques such as deep learning may be impractical for decision-makers due to the lack of data and challenges in justifying and explaining results. In … Read more

    Stability Regularized Cross-Validation

  • Ryan Cory-Wright
  • Andrés Gómez
    • Categories Data-Mining

    We revisit the problem of ensuring strong test-set performance via cross-validation. Motivated by the generalization theory literature, we propose a nested k-fold cross- validation scheme that selects hyperparameters by minimizing a weighted sum of the usual cross-validation metric and an empirical model-stability measure. The weight on the stability term is itself chosen via a nested … Read more