Social Spider Optimization for Preliminary Earthwork-Balanced Highway Alignment Design

Abstract

This study proposes a metaheuristic-based route optimization framework that balances earthworks in highway design by referencing a constant-slope “zero polygon.” The aim is to distribute excavation and embankment volumes evenly between fixed endpoints. The positions of Point of Intersection nodes and curve radii are optimized using the Social Spider Optimization (SSO) algorithm, guided by an objective function that minimizes the weighted signed distances between the route and the zero polygon while enforcing geometric constraints such as minimum curve radius, tangent length, and alignment continuity through penalty terms. Applications on two terrains with varying slopes demonstrate that the calibrated model substantially improves the cut–fill balance compared with both manual and pre-calibration solutions: the absolute difference between excavation and embankment volumes decreased from thousands to hundreds of cubic meters, and the cut–fill ratio fell below 0.1 in representative cases. Coupling a swarm-intelligence search with an interpretable geometric reference line, the framework offers a reproducible decision-support tool for preliminary corridor design. It enhances transparency and reduces reliance on trial-and-error practice. It targets preliminary, open-terrain corridor selection under a constant longitudinal slope without vertical curves, and does not yet incorporate land-use, environmental, or geotechnical constraints.