🤖 AI Summary
Real-world infrastructure networks often exhibit structural incompleteness and require multidimensional evaluation criteria, yet traditional pathfinding methods are limited by their reliance on complete graph structures and scalar optimization objectives. This work proposes the concept of “traversal,” which unifies existing edges with constructible gap connections into a single modeling framework, treating plannable connections as first-class transformation units for the first time. The approach supports non-scalar trade-offs, conditional feasibility checks, and policy calibration. By integrating a parameterized traversal framework, an efficient candidate filtering mechanism, and multidimensional termination criteria, the method bridges graph-based reasoning with engineering feasibility assessment. Empirical validation on data center circuit design and optical communication routing tasks demonstrates its effectiveness, significantly enhancing both expressiveness and practical utility.
📝 Abstract
Classical path search assumes complete graphs and scalar optimization metrics, yet real infrastructure networks are incomplete and require multi-dimensional evaluation. We introduce the concept of traversal: a generalization of paths that combines existing edges with gap transitions, missing but acceptable connections representing links that can be built. This abstraction captures how engineers actually reason about infrastructure: not just what exists, but what can be realized. We present a parametric framework that treats planned connections as first-class transitions, scales to large graphs through efficient candidate filtering, and uses multi-dimensional criteria to decide whether a traversal should continue to be explored or be abandoned. We evaluate the framework through representative scenarios in datacenter circuit design and optical route construction in telecommunication networks, demonstrating conditional feasibility, non-scalarizable trade-offs, and policy calibration capabilities beyond the reach of classical formulations.