AI RESEARCH
Accelerating Discrete Facility Layout Optimization: A Hybrid CDCL and CP-SAT Architecture
arXiv CS.AI
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ArXi:2512.18034v3 Announce Type: replace Discrete facility layout design involves placing physical entities to minimize handling costs while adhering to strict safety and spatial constraints. This combinatorial problem is typically addressed using Mixed Integer Linear Programming (MILP) or Constraint Programming (CP), though these methods often face scalability challenges as constraint density increases. This study systematically evaluates the potential of Conflict-Driven Clause Learning (CDCL) with VSIDS heuristics as an alternative computational engine for discrete layout problems.