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51 changes: 51 additions & 0 deletions .github/workflows/jekyll-gh-pages.yml
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# Sample workflow for building and deploying a Jekyll site to GitHub Pages
name: Deploy Jekyll with GitHub Pages dependencies preinstalled

on:
# Runs on pushes targeting the default branch
push:
branches: ["main"]

# Allows you to run this workflow manually from the Actions tab
workflow_dispatch:

# Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages
permissions:
contents: read
pages: write
id-token: write

# Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued.
# However, do NOT cancel in-progress runs as we want to allow these production deployments to complete.
concurrency:
group: "pages"
cancel-in-progress: false

jobs:
# Build job
build:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v4
- name: Setup Pages
uses: actions/configure-pages@v5
- name: Build with Jekyll
uses: actions/jekyll-build-pages@v1
with:
source: ./
destination: ./_site
- name: Upload artifact
uses: actions/upload-pages-artifact@v3

# Deployment job
deploy:
environment:
name: github-pages
url: ${{ steps.deployment.outputs.page_url }}
runs-on: ubuntu-latest
needs: build
steps:
- name: Deploy to GitHub Pages
id: deployment
uses: actions/deploy-pages@v4
7 changes: 7 additions & 0 deletions .gitignore
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_site/
.sass-cache/
.jekyll-cache/
.jekyll-metadata
# Ignore folders generated by Bundler
.bundle/
vendor/
116 changes: 116 additions & 0 deletions LICENSE
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CC0 1.0 Universal

Statement of Purpose

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27 changes: 27 additions & 0 deletions README.md
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# A Convexification-based Outer-Approximation Method for Convex and Nonconvex MINLP

This repository contains the benchmark results of the paper **"A Convexification-based Outer-Approximation Method for Convex and Nonconvex MINLP"** by Z. Peng, K. Cao, K.C. Furman, C. Li, I.E. Grossmann, and D.E. Bernal. You can view the detailed results on the [web page](https://github.com/SECQUOIA/Convexification-based-OA-Benchmark/).

The implementation is based on MindtPy, the Mixed-Integer Nonlinear Decomposition Toolbox in Pyomo. For more information about MindtPy, please refer to the [Pyomo MindtPy documentation](https://pyomo.readthedocs.io/en/stable/contributed_packages/mindtpy.html).

The benchmark results for each instance are stored as trace files. For more information about trace files, please refer to the [GAMS trace file documentation](https://www.gams.com/latest/docs/UG_SolverUsage.html#UG_SolverUsage_TraceFile).

The software [Paver 2](https://github.com/coin-or/Paver) is used to process the trace files and analyze the performance of the proposed methods in this work.

## MINLP Instances

1. 435 [convex MINLP instances](https://github.com/SECQUOIA/Convexification-based-OA-Benchmark/minlp_instances/convex_instances.txt)
2. 182 [nonconvex MINLP instances](https://github.com/SECQUOIA/Convexification-based-OA-Benchmark/minlp_instances/nonconvex_instances.txt)

## Project Structure

```plaintext
.
├── LICENSE
├── README.md # Project overview and structure
├── _config.yml # Configuration file for GitHub Pages
├── index.md # Main page of the website
├── minlp_instances # Folder containing the list of convex and nonconvex MINLP instances
├── paver_results # Folder containing Paver results
└── trace_file # Folder containing trace files
```
7 changes: 7 additions & 0 deletions _config.yml
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title: Benchmark results
description: A Convexification-Based Outer-Approximation Method for Convex and Nonconvex MINLP
show_downloads: false
google_analytics:
remote_theme: pages-themes/[email protected]
plugins:
- jekyll-remote-theme
18 changes: 18 additions & 0 deletions index.md
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---
layout: default
title: Benchmark Results
---

## Description

The PAVER reports used in the paper: **"A Convexification-based Outer-Approximation Method for Convex and Nonconvex MINLP"** by Z. Peng, K. Cao, K.C. Furman, C. Li, I.E. Grossmann, D.E. Bernal are available here.

## Paver Reports

1. [C-OA for convex instances](https://zedongpeng.github.io/Convexification-based-OA-Benchmark/paver_results/convex/multitree)

2. [C-LP/NLP for convex instances](https://zedongpeng.github.io/Convexification-based-OA-Benchmark/paver_results/convex/singletree)

3. [C-GOA for nonconvex instances](https://zedongpeng.github.io/Convexification-based-OA-Benchmark/paver_results/nonconvex/multitree)

4. [C-GLP/NLP for nonconvex instances](https://zedongpeng.github.io/Convexification-based-OA-Benchmark/paver_results/nonconvex/singletree)
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