From 93b4e11e86e8b9cf66a3fb0c5ed8329a67802a75 Mon Sep 17 00:00:00 2001
From: Furffico <jerrywang0206@gmail.com>
Date: Sun, 20 Oct 2024 20:47:41 +0800
Subject: [PATCH] Build website (2024-10-20 20:47:41, 30e87a4)

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-<!DOCTYPE html><html><head><meta charset=utf-8><meta name=viewport content="width=device-width, initial-scale=1"><title>[NeurIPS 2024] ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution</title><link rel=icon type=image/svg href=static/icon.svg><link rel=preconnect href=https://cdn.jsdelivr.net crossorigin><link rel=preconnect href=https://fonts.googleapis.com crossorigin><link rel=preconnect href=https://cdnjs.cloudflare.com crossorigin><link rel=preload href=static/index.css as=style><link rel=preload href=static/images/reevo.png as=image><link rel=preload href=static/images/show_reflec.png as=image><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/bulma@0.9.1/css/bulma.min.css integrity="sha256-WLKGWSIJYerRN8tbNGtXWVYnUM5wMJTXD8eG4NtGcDM=" crossorigin=anonymous><script defer src=https://cdn.jsdelivr.net/npm/@fancyapps/ui@5.0.36/dist/fancybox/fancybox.umd.min.js></script><script defer src=https://cdn.jsdelivr.net/npm/@fancyapps/ui@5.0.36/dist/carousel/carousel.umd.min.js></script><script defer src=https://cdn.jsdelivr.net/npm/@fancyapps/ui@5.0.36/dist/carousel/carousel.autoplay.umd.min.js></script><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/@fancyapps/ui@5.0.36/dist/carousel/carousel.min.css><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/@fancyapps/ui@5.0.36/dist/fancybox/fancybox.min.css><link rel=stylesheet href=static/index.css><script defer src=https://cdn.jsdelivr.net/npm/clipboard@2.0.11/dist/clipboard.min.js integrity="sha256-4XodgW4TwIJuDtf+v6vDJ39FVxI0veC/kSCCmnFp7ck=" crossorigin=anonymous></script><script defer src=https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@5.15.4/js/all.min.js integrity="sha256-gSqw5G+Gss6YqyQlqyIkuQ0IRZUqGsDVq9c0tiF+mL8=" crossorigin=anonymous></script><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@5.15.4/css/fontawesome.min.css integrity="sha256-BYjRZhSY2ARUPcFTf5eEh3qWK58O88TM7nZet/JUNhE=" crossorigin=anonymous><link rel=stylesheet href=https://cdn.jsdelivr.net/gh/jpswalsh/academicons@1/css/academicons.min.css><link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro" rel=stylesheet><link rel=stylesheet href=https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/styles/default.min.css><script defer src=https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/highlight.min.js></script><script defer src=https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/languages/bash.min.js></script><script defer src=https://cloud.umami.is/script.js data-website-id=c18ebe0b-2d3c-48ff-9cef-62c34bbadb04></script></head><body><section class=hero id=title><div class=hero-body><div class="container is-max-desktop" style=max-width:1200px><div class="columns is-centered"><div class="column has-text-centered"><h1 class="title is-1 publication-title">ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution</h1><div class="is-size-5 publication-authors"><span class=author-block><a href=https://henry-yeh.github.io/ target=_blank>Haoran Ye</a><sup>1</sup>,</span><span class=author-block><a href=https://github.com/Furffico target=_blank>Jiarui Wang</a><sup>2</sup>,</span><span class=author-block><a href=https://zhiguangcaosg.github.io/ target=_blank>Zhiguang Cao</a><sup>3</sup>,</span><span class=author-block><a href=https://fedebotu.github.io/ target=_blank>Federico Berto</a><sup>4</sup>,</span><span class=author-block><a href=https://cbhua.github.io/ target=_blank>Chuanbo Hua</a><sup>4</sup>,</span><span class=author-block><a href=https://sites.google.com/view/haeyeon-rachel-kim target=_blank>Haeyeon Kim</a><sup>4</sup>,</span><span class=author-block><a href=https://pure.kaist.ac.kr/en/persons/jinkyoo-park target=_blank>Jinkyoo Park</a><sup>4</sup>,</span><span class=author-block><a href=https://www.cis.pku.edu.cn/info/1362/2256.htm target=_blank>Guojie Song</a><sup>1,5</sup></span></div><div class="is-size-6 publication-authors"><span class=author-block style=margin-right:.5em><sup>1 </sup>National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University</span><br><span class=author-block style=margin-right:.5em><sup>2 </sup>Southeast University</span><span class=author-block style=margin-right:.5em><sup>3 </sup>Singapore Management University</span><span class=author-block style=margin-right:.5em><sup>4 </sup>KAIST</span><span class=author-block style=margin-right:.5em><sup>5 </sup>PKU-Wuhan Institute for Artificial Intelligence</span><span class=author-block style=margin-right:.5em><sup>† </sup><a href=https://github.com/ai4co target=_blank>AI4CO</a></span><br><b class="author-block is-size-5" style="padding:1ex 0">NeurIPS 2024</b><span class=eql-cntrb><br><sup>†</sup>Work made with contributions from the AI4CO open research community.</span></div><div class="column has-text-centered"><div class=publication-links><span class=link-block><a href=https://arxiv.org/pdf/2402.01145 target=_blank class="external-link button is-normal is-rounded is-dark"><span class=icon><i class="fas fa-file-pdf"></i></span><span>Paper</span></a></span><span class=link-block><a href=https://arxiv.org/abs/2402.01145 target=_blank class="external-link button is-normal is-rounded is-dark"><span class=icon><i class="ai ai-arxiv"></i></span><span>arXiv</span></a></span><span class=link-block><a href=https://github.com/ai4co/reevo target=_blank class="external-link button is-normal is-rounded is-dark"><span class=icon><i class="fab fa-github"></i></span><span>Code</span></a></span><span class=link-block><a href=https://join.slack.com/t/rl4co/shared_invite/zt-1ytz2c1v4-0IkQ8NQH4TRXIX8PrRmDhQ target=_blank class="external-link button is-normal is-rounded is-dark"><span class=icon><i class="fab fa-slack"></i></span><span>Slack</span></a></span></div></div><div class="column has-text-centered is-size-5"><b>Give ReEvo 5 minutes, and get a state-of-the-art algorithm in return!</b></div></div></div></div></div></section><section class="section hero is-light red-link" id=abstract><div class="container is-max-desktop"><div class="columns is-centered has-text-centered"><div class="column is-four-fifths"><h2 class="title is-3">Abstract</h2><div class="content has-text-justified"><p>The omnipresence of NP-hard combinatorial optimization problems (COPs) compels domain experts to engage in trial-and-error heuristic design. The long-standing endeavor of design automation has gained new momentum with the rise of large language models (LLMs). This paper introduces Language Hyper-Heuristics (LHHs), an emerging variant of Hyper-Heuristics that leverages LLMs for heuristic generation, featuring minimal manual intervention and open-ended heuristic spaces. To empower LHHs, we present <b>Reflective Evolution</b> (<span style=font-family:monospace>ReEvo</span>), a novel integration of evolutionary search for efficiently exploring the heuristic space, and LLM reflections to provide verbal gradients within the space. Across five heterogeneous algorithmic types, six different COPs, and both white-box and black-box views of COPs, <span style=font-family:monospace>ReEvo</span> yields state-of-the-art and competitive meta-heuristics, evolutionary algorithms, heuristics, and neural solvers, while being more sample-efficient than prior LHHs. </p></div></div></div></div></section><section class="hero is-small" id=carousel><div class=hero-body><div class=container><div class=f-carousel id=paper-carousel><div class="f-carousel__slide carousel-slide"><div><a href=static/images/reevo.png data-fancybox=carousel-1 data-caption='<span style="font-family:monospace">ReEvo</span> pipeline.'><img src=static/images/reevo.png alt='<span style="font-family:monospace">ReEvo</span> pipeline.'></a><h2 class="subtitle has-text-centered" style=margin-top:1ex><span style=font-family:monospace>ReEvo</span> pipeline. </h2></div></div><div class="f-carousel__slide carousel-slide"><div><a href=static/images/show_reflec.png data-fancybox=carousel-1 data-caption="Examples of reflections for black-box TSP."><img src=static/images/show_reflec.png alt="Examples of reflections for black-box TSP."></a><h2 class="subtitle has-text-centered" style=margin-top:1ex> Examples of reflections for black-box TSP. </h2></div></div></div></div></div></section><section class="section hero is-light red-link" id=usage><div class="container is-max-desktop content" style=width:100%><h2 class=title>Usage 🔑</h2><h3>Get Started</h3><div class=code-container style=background-color:white><pre><code class="code-content language-bash" style=background-color:white id=code-content-1>$ git clone git@github.com:ai4co/reevo.git # download reevo code
+<!DOCTYPE html><html><head><meta charset=utf-8><meta property=og:url content=https://ai4co.github.io/reevo><meta property=og:title content="ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution"><meta name=twitter:title content="[NeurIPS 2024] ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution"><meta name=description content="We introduce ReEvo, a novel approach that harnesses the power of LLMs as Hyper-Heuristics for solving complex combinatorial optimization problems with minimal manual intervention."><meta property=og:description content="We introduce ReEvo, a novel approach that harnesses the power of LLMs as Hyper-Heuristics for solving complex combinatorial optimization problems with minimal manual intervention."><meta name=twitter:description content="We introduce ReEvo, a novel approach that harnesses the power of LLMs as Hyper-Heuristics for solving complex combinatorial optimization problems with minimal manual intervention."><meta name=keywords content="Automatic Algorithm Generation, Evolutionary Algorithms, LLM Agent, Hyper Heuristics"><meta property=og:image content=static/images/reevo.png><meta name=twitter:image content=static/images/reevo.png><meta name=twitter:card content=static/images/reevo.png><meta name=viewport content="width=device-width, initial-scale=1"><title>[NeurIPS 2024] ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution</title><link rel=icon type=image/svg href=static/icon.svg><link rel=preconnect href=https://cdn.jsdelivr.net crossorigin><link rel=preconnect href=https://fonts.googleapis.com crossorigin><link rel=preconnect href=https://cdnjs.cloudflare.com crossorigin><link rel=preload href=static/index.css as=style><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/bulma@0.9.1/css/bulma.min.css integrity="sha256-WLKGWSIJYerRN8tbNGtXWVYnUM5wMJTXD8eG4NtGcDM=" crossorigin=anonymous><link rel=preload href=static/images/reevo.png as=image><link rel=preload href=static/images/show_reflec.png as=image><script defer src=https://cdn.jsdelivr.net/npm/@fancyapps/ui@5.0.36/dist/fancybox/fancybox.umd.min.js></script><script defer src=https://cdn.jsdelivr.net/npm/@fancyapps/ui@5.0.36/dist/carousel/carousel.umd.min.js></script><script defer src=https://cdn.jsdelivr.net/npm/@fancyapps/ui@5.0.36/dist/carousel/carousel.autoplay.umd.min.js></script><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/@fancyapps/ui@5.0.36/dist/carousel/carousel.min.css><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/@fancyapps/ui@5.0.36/dist/fancybox/fancybox.min.css><link rel=stylesheet href=static/index.css><script defer src=https://cdn.jsdelivr.net/npm/clipboard@2.0.11/dist/clipboard.min.js integrity="sha256-4XodgW4TwIJuDtf+v6vDJ39FVxI0veC/kSCCmnFp7ck=" crossorigin=anonymous></script><script defer src=https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@5.15.4/js/all.min.js integrity="sha256-gSqw5G+Gss6YqyQlqyIkuQ0IRZUqGsDVq9c0tiF+mL8=" crossorigin=anonymous></script><link rel=stylesheet href=https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@5.15.4/css/fontawesome.min.css integrity="sha256-BYjRZhSY2ARUPcFTf5eEh3qWK58O88TM7nZet/JUNhE=" crossorigin=anonymous><link rel=stylesheet href=https://cdn.jsdelivr.net/gh/jpswalsh/academicons@1/css/academicons.min.css><link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro" rel=stylesheet><link rel=stylesheet href=https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/styles/default.min.css><script defer src=https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/highlight.min.js></script><script defer src=https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/languages/bash.min.js></script><script defer src=https://cloud.umami.is/script.js data-website-id=c18ebe0b-2d3c-48ff-9cef-62c34bbadb04></script></head><body><section class=hero id=title><div class=hero-body><div class="container is-max-desktop" style=max-width:1200px><div class="columns is-centered"><div class="column has-text-centered"><h1 class="title is-2 publication-title">ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution</h1><div class="is-size-5 publication-authors"><span class=author-block><a href=https://henry-yeh.github.io/ target=_blank data-umami-event="click-link:Haoran Ye">Haoran Ye</a><sup>1</sup>,</span><span class=author-block><a href=https://github.com/Furffico target=_blank data-umami-event="click-link:Jiarui Wang">Jiarui Wang</a><sup>2</sup>,</span><span class=author-block><a href=https://zhiguangcaosg.github.io/ target=_blank data-umami-event="click-link:Zhiguang Cao">Zhiguang Cao</a><sup>3</sup>,</span><span class=author-block><a href=https://fedebotu.github.io/ target=_blank data-umami-event="click-link:Federico Berto">Federico Berto</a><sup>4</sup>,</span><span class=author-block><a href=https://cbhua.github.io/ target=_blank data-umami-event="click-link:Chuanbo Hua">Chuanbo Hua</a><sup>4</sup>,</span><span class=author-block><a href=https://sites.google.com/view/haeyeon-rachel-kim target=_blank data-umami-event="click-link:Haeyeon Kim">Haeyeon Kim</a><sup>4</sup>,</span><span class=author-block><a href=https://pure.kaist.ac.kr/en/persons/jinkyoo-park target=_blank data-umami-event="click-link:Jinkyoo Park">Jinkyoo Park</a><sup>4</sup>,</span><span class=author-block><a href=https://www.cis.pku.edu.cn/info/1362/2256.htm target=_blank data-umami-event="click-link:Guojie Song">Guojie Song</a><sup>1,5</sup></span></div><div class="is-size-6 publication-authors"><span class=author-block style=margin-right:.5em><sup>1 </sup>National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University</span><br><span class=author-block style=margin-right:.5em><sup>2 </sup>Southeast University</span><span class=author-block style=margin-right:.5em><sup>3 </sup>Singapore Management University</span><span class=author-block style=margin-right:.5em><sup>4 </sup>KAIST</span><span class=author-block style=margin-right:.5em><sup>5 </sup>PKU-Wuhan Institute for Artificial Intelligence</span><span class=author-block style=margin-right:.5em><sup>† </sup><a href=https://github.com/ai4co target=_blank data-umami-event=click-link:AI4CO>AI4CO</a></span><br><b class="author-block is-size-5" style="padding:1ex 0">NeurIPS 2024</b><span class=eql-cntrb><br><sup>†</sup>Work made with contributions from the AI4CO open research community.</span></div><div class="column has-text-centered"><div class=publication-links><span class=link-block><a href=https://arxiv.org/pdf/2402.01145 target=_blank class="external-link button is-normal is-rounded is-dark" data-umami-event=click-link:pdf><span class=icon><i class="fas fa-file-pdf"></i></span><span>Paper</span></a></span><span class=link-block><a href=https://arxiv.org/abs/2402.01145 target=_blank class="external-link button is-normal is-rounded is-dark" data-umami-event=click-link:arXiv><span class=icon><i class="ai ai-arxiv"></i></span><span>arXiv</span></a></span><span class=link-block><a href=https://github.com/ai4co/reevo target=_blank class="external-link button is-normal is-rounded is-dark" data-umami-event=click-link:github><span class=icon><i class="fab fa-github"></i></span><span>Code</span></a></span><span class=link-block><a href=https://join.slack.com/t/rl4co/shared_invite/zt-1ytz2c1v4-0IkQ8NQH4TRXIX8PrRmDhQ target=_blank class="external-link button is-normal is-rounded is-dark" data-umami-event=click-link:Slack><span class=icon><i class="fab fa-slack"></i></span><span>Slack</span></a></span></div></div><div class="column has-text-centered is-size-5"><b>Give ReEvo 5 minutes, and get a state-of-the-art algorithm in return!</b></div></div></div></div></div></section><section class="section hero is-light red-link" id=abstract><div class="container is-max-desktop"><div class="columns is-centered has-text-centered"><div class="column is-four-fifths"><h2 class="title is-3">Abstract</h2><div class="content has-text-justified"><p>The omnipresence of NP-hard combinatorial optimization problems (COPs) compels domain experts to engage in trial-and-error heuristic design. The long-standing endeavor of design automation has gained new momentum with the rise of large language models (LLMs). This paper introduces Language Hyper-Heuristics (LHHs), an emerging variant of Hyper-Heuristics that leverages LLMs for heuristic generation, featuring minimal manual intervention and open-ended heuristic spaces. To empower LHHs, we present <b>Reflective Evolution</b> (<span style=font-family:monospace>ReEvo</span>), a novel integration of evolutionary search for efficiently exploring the heuristic space, and LLM reflections to provide verbal gradients within the space. Across five heterogeneous algorithmic types, six different COPs, and both white-box and black-box views of COPs, <span style=font-family:monospace>ReEvo</span> yields state-of-the-art and competitive meta-heuristics, evolutionary algorithms, heuristics, and neural solvers, while being more sample-efficient than prior LHHs. </p></div></div></div></div></section><section class="hero is-small" id=carousel><div class=hero-body><div class=container><div class=f-carousel id=paper-carousel><div class="f-carousel__slide carousel-slide"><div><a href=static/images/reevo.png data-fancybox=carousel-1 data-caption='<span style="font-family:monospace">ReEvo</span> pipeline.'><img src=static/images/reevo.png alt='<span style="font-family:monospace">ReEvo</span> pipeline.'></a><h2 class="subtitle has-text-centered" style=margin-top:1ex><span style=font-family:monospace>ReEvo</span> pipeline. </h2></div></div><div class="f-carousel__slide carousel-slide"><div><a href=static/images/show_reflec.png data-fancybox=carousel-1 data-caption="Examples of reflections for black-box TSP."><img src=static/images/show_reflec.png alt="Examples of reflections for black-box TSP."></a><h2 class="subtitle has-text-centered" style=margin-top:1ex> Examples of reflections for black-box TSP. </h2></div></div></div></div></div></section><section class="section hero is-light red-link" id=usage><div class="container is-max-desktop content" style=width:100%><h2 class=title>Usage 🔑</h2><h3>Get Started</h3><div class=code-container style=background-color:white><pre><code class="code-content language-bash" style=background-color:white id=code-content-1>$ git clone git@github.com:ai4co/reevo.git # download reevo code
 $ cd reevo
 $ python3 -m venv ./venv            # [optional] create virtual environment
 $ source ./venv/bin/activate        # [optional] activate virtual environment
@@ -16,14 +16,14 @@
     booktitle={Advances in Neural Information Processing Systems},
     year={2024},
     note={\url{https://github.com/ai4co/reevo}}
-}</code></pre><button class=copy-button alt="Copy to clipboard" data-clipboard-target=#code-content-bibtex><span class="copy-icon before-copy"><i class="fa fa-copy"></i></span><span class="copy-icon after-copy"><i class="fas fa-check"></i></span></button></div></div></section><section class="section hero is-light red-link" id=news><div class="container is-max-desktop content" style=width:100%><h2 class=title>News 📰</h2><div class=has-text-justified><table><tbody><tr><th>Sep. 2024</th><td><em>ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution</em> has been accepted at NeurIPS 2024 🥳</td></tr><tr><th>May 2024</th><td>We release a new paper version</td></tr><tr><th>Apr. 2024</th><td>Novel use cases for Neural Combinatorial Optimization (NCO) and Electronic Design Automation (EDA)</td></tr><tr><th>Feb. 2024</th><td>We are excited to release <em>ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution</em> 🚀</td></tr></tbody></table></div></div></section><footer class=footer><div class=container><div class="columns is-centered"><div class="column is-8"><div class=content><p> This page was built using the <a href=https://github.com/ai4co/research-project-page-template target=_blank>Research Project Page Template</a> which is based on the <a href=https://github.com/eliahuhorwitz/Academic-project-page-template target=_blank>Academic Project Page Template</a> and the <a href=https://nerfies.github.io target=_blank>Nerfies project page</a>. You are free to borrow the of this website, we just ask that you link back to this page in the footer. This website is licensed under a <a rel=license href=http://creativecommons.org/licenses/by-sa/4.0/ target=_blank>Creative Commons Attribution-ShareAlike 4.0 International License</a>. </p></div></div></div></div></footer><script>
+}</code></pre><button class=copy-button alt="Copy to clipboard" data-clipboard-target=#code-content-bibtex data-umami-event=copy-citation><span class="copy-icon before-copy"><i class="fa fa-copy"></i></span><span class="copy-icon after-copy"><i class="fas fa-check"></i></span></button></div></div></section><section class="section hero is-light red-link" id=news><div class="container is-max-desktop content" style=width:100%><h2 class=title>News 📰</h2><div class=has-text-justified><table><tbody><tr><th>Sep. 2024</th><td><em>ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution</em> has been accepted at NeurIPS 2024 🥳</td></tr><tr><th>May 2024</th><td>We release a new paper version</td></tr><tr><th>Apr. 2024</th><td>Novel use cases for Neural Combinatorial Optimization (NCO) and Electronic Design Automation (EDA)</td></tr><tr><th>Feb. 2024</th><td>We are excited to release <em>ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution</em> 🚀</td></tr></tbody></table></div></div></section><footer class=footer><div class=container><div class="columns is-centered"><div class="column is-8"><div class=content><p> This page was built using the <a href=https://github.com/ai4co/research-project-page-template target=_blank>Research Project Page Template</a> which is based on the <a href=https://github.com/eliahuhorwitz/Academic-project-page-template target=_blank>Academic Project Page Template</a> and the <a href=https://nerfies.github.io target=_blank>Nerfies project page</a>. You are free to borrow the of this website, we just ask that you link back to this page in the footer. This website is licensed under a <a rel=license href=http://creativecommons.org/licenses/by-sa/4.0/ target=_blank>Creative Commons Attribution-ShareAlike 4.0 International License</a>. </p></div></div></div></div></footer><script>
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Sep. 2024	ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution has been accepted at NeurIPS 2024 🥳
May 2024	We release a new paper version
Apr. 2024	Novel use cases for Neural Combinatorial Optimization (NCO) and Electronic Design Automation (EDA)
Feb. 2024	We are excited to release ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution 🚀