Enhancing heuristic bubble algorithm with simulated annealing

In this study, a new way to improve the Heuristic Bubble Algorithm (HBA) is presented. HBA is a nature-inspired algorithm, which is a new approach to and initially implemented for, vehicle routing problems of pickup and delivery (VRPPD). Later, it was reinforced to solve other routing problems, such as vehicle routing problem with time windows (VRPTW), and vehicle routing problem with stochastic demands (VRPSD). HBA is a greedy algorithm. It will mostly find local optimal solutions. The proposed method is an improvement over HBA enabling it to reach the global minimum. It uses specialized simulated annealing methods in its operators. A well-known data-set is used to benchmark the proposed method. Better results over HBA and some best results in literature are recorded.