Thinklab-SJTU/COExpander
Official implementation of "COExpander: Adaptive Solution Expansion for Combinatorial Optimization".
COExpander is a tool for tackling complex combinatorial optimization problems, like finding the shortest routes or efficient resource allocations. It takes in large problem instances, often represented as graphs with many nodes (up to 10,000), and outputs high-quality, optimized solutions. This is useful for researchers and practitioners who need to solve difficult planning or scheduling challenges that are too large or intricate for traditional methods.
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Use this if you are working with large-scale combinatorial optimization problems (e.g., maximum independent set, traveling salesman, minimum vertex cover) and need to find state-of-the-art solutions efficiently.
Not ideal if you are looking for an off-the-shelf application to solve specific business problems without any programming or machine learning setup.
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Jun 28, 2025
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