BALANCING EXPLORATION AND EXPLOITATION IN ANT COLONY SYSTEM FOR WASTE COLLECTION VEHICLE ROUTING PROBLEM WITH TIME WINDOWS

Abstract

The Vehicle Routing Problem is a combinatorial optimization problem in logistics aiming to determine optimal routes for a fleet of vehicles servicing a set of customers. The vital challenge in optimizing route efficiency includes reducing total distance, satisfying demand, and vehicle capacity constraints. The Vehicle Routing Problem Time Window introduces time window constraints that reflect real-world scenarios, requiring each customer to be serviced within a specified time interval, thus significantly increasing problem complexity. As the global waste generation is expected to continue to grow worldwide over the coming decades, the demand for the Waste Collection Vehicle Routing Problem with time window is essential. Ant Colony System (ACS) produces high-quality solutions, especially for complex scenarios. However, it leads to the issues of premature convergence and stagnation. This research explored insights using the waste collection benchmark dataset.   To further enhance the result, the parameter settings of the parameter values were tuned during testing. The aim is to improve the solution quality by utilizing the exploration and exploitation capabilities of ACS. Experimental results demonstrate performance improvement in reducing the travel distance. Future research should explore the use of hybrid algorithms in actual platforms, considering sustainable logistics, and contribute to a scalable solution for logistics.