Resources Relocation Support Strategy Based on a Modified Genetic Algorithm for Bike-Sharing Systems

In recent decades, special attention has been given to the adverse effects of traffic congestion. Bike-sharing systems, as a part broader category shared transportation are seen viable solutions these problems. Even if quality service in bike-sharing systems were permanently improved, there would still be some issues that needed new and more efficient solutions. One refers rebalancing operations follow bike depletion phenomenon affects most stations during shorter or longer time periods. Current work develops two-step method perform effective bike-sharing. The core elements fuzzy logic-controlled genetic algorithm for station prioritization an inference mechanism aiming do assignment between trucks. solution was tested on data collected from Citi Bike New York system. proposed shows overall superior performance compared other algorithms specific capacitated vehicle routing problems: standard algorithm, ant colony optimization, Tabu search improved Harris Hawks optimization scenarios. Since is independent past measurements, it applies any potential