Chaotic Search Method Using Effective Adaptive Time Penalty Coefficients for Vehicle Routing Problem with Time Windows.

The surge in online shopping has increased the demand for home delivery, leading to a shortage of delivery drivers. This situation compels logistics companies to devise efficient delivery routes, considering delivery times, number of vehicles, and fuel costs. This issue is called the Vehicle Routing Problem with Time Windows (VRPTW). Recent research indicates that the chaotic search (CS) method with adaptive penalty coefficients (APCs) can efficiently solve VRPTW. The CS method with APCs (CS-APC) achieves an efficient solution search by diversifying and centralizing solutions in accordance with the search situation. However, when the solution diversifies towards the end of the search, the variance of solutions obtained by CS-APC increases. In this study, we propose a CS method using APCs based on temperature annealing (APCT). The use of APCT strengthens solution centralization via the search time temperature, thereby improving the quality of solutions. Numerical experiments confirm that our proposed method finds solutions with fewer vehicles and shorter travel distances than when using the conventional method. [ABSTRACT FROM AUTHOR]