julia

MultiObjectiveAlgorithms.jl: a Julia package for solving multi-objective optimization problems

  • Oscar Dowson
  • Xavier Gandibleux
  • Gökhan Kof
    • Categories Multi-Criteria Optimization, Optimization Software and Modeling Systems Tags , , ,

    We present MultiObjectiveAlgorithms.jl, an open-source Julia library for solving multi-objective optimization problems written in JuMP. MultiObjectiveAlgorithms.jl implements a number of different solution algorithms, which all rely on an iterative scalarization of the problem from a multi-objective optimization problem to a sequence of single-objective subproblems. As part of this work, we extended JuMP to support vector-valued … 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

    Multiple Kernel Learning-Aided Column-and-Constraint Generation Method

  • Biao Han
    • Categories Applications - OR and Management Sciences, Optimization in Data Science, Robust Optimization Tags , , , ,

    Two-stage robust optimization (two-stage RO), due to its ability to balance robustness and flexibility, has been widely used in various fields for decision-making under uncertainty. This paper proposes a multiple kernel learning (MKL)-aided column-and-constraint generation (CCG) method to address this issue in the context of data-driven decision optimization, and releases a corresponding registered Julia package, … Read more

    S2MPJ and CUTEst optimization problems for Matlab, Python and Julia

  • Serge Gratton
  • Philippe L. Toint
    • Categories Nonlinear Optimization, Optimization Software Benchmark Tags , , , , ,

    A new decoder for the SIF test problems of the \cutest\ collection is described, which produces problem files allowing the computation of values and derivatives of the objective function and constraints of most \cutest\ problems directly within “native” Matlab, Python or Julia, without any additional installation or interfacing with MEX files or Fortran programs. When … Read more

    BilevelJuMP.jl: Modeling and Solving Bilevel Optimization in Julia

  • Joaquim Dias Garcia
  • Guilherme Bodin
  • Alexandre Street
    • Categories Complementarity and Variational Inequalities, Modeling Languages and Systems, Optimization Software and Modeling Systems Tags , , , ,

    In this paper we present BilevelJuMP, a new Julia package to support bilevel optimization within the JuMP framework. The package is a Julia library that enables the user to describe both upper and lower-level optimization problems using the JuMP algebraic syntax. Due to the generality and flexibility our library inherits from JuMP’s syntax, our package … Read more

    JuDGE.jl: a Julia package for optimizing capacity expansion

  • Regan Baucke
  • Anthony Downward
  • Andrew B. Philpott
    • Categories Applications - OR and Management Sciences, Optimization Software and Modeling Systems, Stochastic Programming Tags , , , ,

    We present JuDGE.jl, an open-source Julia package for solving multistage stochastic capacity expansion problems using Dantzig-Wolfe decomposition. Models for JuDGE.jl are built using JuMP, the algebraic modelling language in Julia, and solved by repeatedly applying mixed-integer programming. We illustrate JuDGE.jl by formulating and solving a toy knapsack problem, and demonstrate the performance of JuDGE.jl on … Read more