Reference Card: We will show off some new features in Convex.jl, solve a few example problems, and discuss development plans for the future. To increase transparency and partnership opportunities, the Department of Energy funded an open source release of NREL ...

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Real-world problems require sophisticated methodologies providing feasible and efficient solutions. To increase transparency and partnership opportunities, the Department of Energy funded an open source release of NREL ...

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We will show off some new features in Convex.jl, solve a few example problems, and discuss development plans for the future.

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  • We will show off some new features in Convex.jl, solve a few example problems, and discuss development plans for the future.
  • Real-world problems require sophisticated methodologies providing feasible and efficient solutions.
  • To increase transparency and partnership opportunities, the Department of Energy funded an open source release of NREL ...

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Keynote: Conic Optimization in Julia and JuMP | Juan Pablo Vielma | JuliaCon 2020
JuMP-dev 2019 | Juan Pablo Vielma | Introductory Tutorial on Julia and JuMP
Polynomial and Moment Optimization in Julia and JuMP | JuliaCon 2019
Multi-objective Optimization with JuMP | Xavier Gandibleux | JuliaCon 2023
The JuMP ecosystem for mathematical optimization | Juan Pablo Vielma | JuliaCon 2018
Efficient Constrained Optimization using ConicSolve.jl | Leong | JuliaCon Global 2025
JuliaCon 2020 | Migrating to JuMP: Leaving Behind Domain Specific Languages | Josiah Pohl
JuliaCon 2020 | Convex.jl: where are we and where do we want to go? | Eric P. Hanson
Interior-point Conic Optimization with Clarabel.jl | Paul Goulart | JuliaCon 2022
Metaheuristics.jl: Towards Any Optimization | Jesús Mejía | JuliaCon 2022
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Keynote: Conic Optimization in Julia and JuMP | Juan Pablo Vielma | JuliaCon 2020

Keynote: Conic Optimization in Julia and JuMP | Juan Pablo Vielma | JuliaCon 2020

Read more details and related context about Keynote: Conic Optimization in Julia and JuMP | Juan Pablo Vielma | JuliaCon 2020.

JuMP-dev 2019 | Juan Pablo Vielma | Introductory Tutorial on Julia and JuMP

JuMP-dev 2019 | Juan Pablo Vielma | Introductory Tutorial on Julia and JuMP

Read more details and related context about JuMP-dev 2019 | Juan Pablo Vielma | Introductory Tutorial on Julia and JuMP.

Polynomial and Moment Optimization in Julia and JuMP | JuliaCon 2019

Polynomial and Moment Optimization in Julia and JuMP | JuliaCon 2019

Read more details and related context about Polynomial and Moment Optimization in Julia and JuMP | JuliaCon 2019.

Multi-objective Optimization with JuMP | Xavier Gandibleux | JuliaCon 2023

Multi-objective Optimization with JuMP | Xavier Gandibleux | JuliaCon 2023

Read more details and related context about Multi-objective Optimization with JuMP | Xavier Gandibleux | JuliaCon 2023.

The JuMP ecosystem for mathematical optimization | Juan Pablo Vielma | JuliaCon 2018

The JuMP ecosystem for mathematical optimization | Juan Pablo Vielma | JuliaCon 2018

Read more details and related context about The JuMP ecosystem for mathematical optimization | Juan Pablo Vielma | JuliaCon 2018.

Efficient Constrained Optimization using ConicSolve.jl | Leong | JuliaCon Global 2025

Efficient Constrained Optimization using ConicSolve.jl | Leong | JuliaCon Global 2025

Read more details and related context about Efficient Constrained Optimization using ConicSolve.jl | Leong | JuliaCon Global 2025.

JuliaCon 2020 | Migrating to JuMP: Leaving Behind Domain Specific Languages | Josiah Pohl

JuliaCon 2020 | Migrating to JuMP: Leaving Behind Domain Specific Languages | Josiah Pohl

To increase transparency and partnership opportunities, the Department of Energy funded an open source release of NREL ...

JuliaCon 2020 | Convex.jl: where are we and where do we want to go? | Eric P. Hanson

JuliaCon 2020 | Convex.jl: where are we and where do we want to go? | Eric P. Hanson

We will show off some new features in Convex.jl, solve a few example problems, and discuss development plans for the future.

Interior-point Conic Optimization with Clarabel.jl | Paul Goulart | JuliaCon 2022

Interior-point Conic Optimization with Clarabel.jl | Paul Goulart | JuliaCon 2022

Read more details and related context about Interior-point Conic Optimization with Clarabel.jl | Paul Goulart | JuliaCon 2022.

Metaheuristics.jl: Towards Any Optimization | Jesús Mejía | JuliaCon 2022

Metaheuristics.jl: Towards Any Optimization | Jesús Mejía | JuliaCon 2022

Real-world problems require sophisticated methodologies providing feasible and efficient solutions. Metaheuristics are algorithms ...