An Effective Optimization Algorithm for the Vehicle Routing Problem with Simultaneous Pickup and Delivery

The Rank-Based Ant System (RAS) is a probabilistic technique that simulates the ant’s food-hunting behavior and is used for solving problems that do not have a known efficient algorithm. This paper proposes a combined RAS mixed with two local searches for solving the vehicle routing problem with simultaneously pickup and delivery as one of the most important combinatorial optimization problems. In this problem, vehicles are not only required to deliver goods to customers but also to pick some goods up at customer locations. This proposed algorithm is different with common RAS on the transition rule and updating pheromone. This process avoids the premature convergence, escapes from local optimum, and makes better solutions. The proposed algorithm is tested on twenty eight standard instances available from the literature. The computational result shows that the proposed algorithm is competitive with other meta-heuristic algorithms for solving vehicle routing problem with simultaneously pickup and delivery.