Entropy-Driven Drift as a Source of Optimization Difficulty in Combinatorial Spaces
For researchers studying optimization in high-dimensional combinatorial spaces, this work provides a new trajectory-level framework that explains why search algorithms struggle, even in symmetric landscapes.
The paper identifies entropy-driven drift as a structural mechanism that biases search trajectories toward high-entropy regions in combinatorial spaces, independent of objective variation. This drift causes a discrepancy between rapid mixing and slow hitting, making target-reaching trajectories atypical and thus explaining optimization difficulty.
Understanding the origin of optimization difficulty in high-dimensional combinatorial spaces remains a fundamental problem. Existing perspectives typically characterize difficulty in terms of properties of states, their connectivity, or distributions over states. However, search algorithms operate as stochastic processes evolving over time, and optimization is inherently a trajectory-level phenomenon. This motivates a shift from state-based to trajectory-based analysis. In this work, we adopt a trajectory-based perspective and analyze search dynamics through the evolution of a distance process. We identify a structural mechanism, which we term entropy-driven drift. This mechanism systematically biases trajectories toward high-entropy regions. This drift arises from asymmetry in local transitions induced by the underlying graph structure, independent of objective variation. In the absence of objective variation, trajectories that reach the target are atypical under the induced dynamics, leading to a discrepancy between rapid mixing and slow hitting. We formalize this mechanism in a canonical combinatorial setting with a highly symmetric underlying graph, where the symmetry allows explicit characterization of the induced drift. The mechanism highlights entropy-driven drift as a source of optimization difficulty and provides a trajectory-level framework for understanding search dynamics in combinatorial spaces.