Optimizing logistics park layouts through simulation and adaptive genetic algorithms

• Novel adaptive genetic algorithm optimizes logistics park layouts. • Solves optimal road network selection for specialized functional zones. • Adaptive crossover and mutation operations yield superior solutions. • Grid and circular layouts outperform others in simulation comparisons. • Aids planners in developing sustainable, efficient transportation networks. This paper presents an innovative approach to the design of logistics park layouts using an Adaptive Genetic Algorithm (GA). Logistics park layout optimization is a complex problem with significant implications for freight transportation efficiency and overall park functionality. In this study, we address the challenge of selecting the most suitable road network layout by considering the unique characteristics of the logistics park and its functional areas. The Adaptive GA incorporates a sophisticated strategy for initial population generation and an adaptive crossover and mutation operation, leading to improved solutions. Through rigorous simulations and evaluations, we compare different road network layouts, highlighting the advantages of both grid and circular layouts. The findings provide valuable insights for logistics park planners and decision-makers, contributing to sustainable and efficient transportation networks.