用树状探索与双点思维提升复杂工程方案设计效率
DeepSolution: Boosting Complex Engineering Solution Design via Tree-based Exploration and Bi-point Thinking
- 构建树状搜索路径，双向思考关键约束条件
- 在新基准SolutionBench上达到当前最佳性能
- 适合需要高可靠性工程设计的工业场景
复杂工程问题求解对人类生产活动至关重要。然而，现有检索增强生成（RAG）研究尚未充分覆盖复杂工程方案设计任务。为此，我们提出新基准SolutionBench，用于评估系统生成满足多重复杂约束的完整可行方案的能力。为进一步推进该领域发展，我们提出SolutionRAG系统，结合树状探索与双点思维机制，生成可靠方案。大量实验表明，SolutionRAG在SolutionBench上取得当前最优表现，展现出在真实应用场景中提升复杂工程设计自动化与可靠性的潜力。
原文摘要 · Abstract (English)
Designing solutions for complex engineering challenges is crucial in human production activities. However, previous research in the retrieval-augmented generation (RAG) field has not sufficiently addressed tasks related to the design of complex engineering solutions. To fill this gap, we introduce a new benchmark, SolutionBench, to evaluate a system's ability to generate complete and feasible solutions for engineering problems with multiple complex constraints. To further advance the design of complex engineering solutions, we propose a novel system, SolutionRAG, that leverages the tree-based exploration and bi-point thinking mechanism to generate reliable solutions. Extensive experimental results demonstrate that SolutionRAG achieves state-of-the-art (SOTA) performance on the SolutionBench, highlighting its potential to enhance the automation and reliability of complex engineering solution design in real-world applications.
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