An evolutionary approach for the selective pickup and delivery problem

The pickup and delivery problem addresses the real-world issues in logistic industry and establishes an important category of vehicle routing problems. The problem is to find the shortest route to collect and distribute objects under the assumption that the total supply and the total demand are in equilibrium. This study formulates a new problem, called the selective pickup and delivery problem (SPDP), by relaxing the constraint that all pickup nodes must be visited. Specifically, the SPDP aims to find the shortest route that can supply delivery nodes with required commodities from some pickup nodes. This problem can substantially reduce the transportation cost and fits some real-world scenarios. Furthermore, this study proposes a genetic algorithm (GA) to resolve the SPDP. A repair strategy is designed for the GA to deal with the constraint in the SPDP. Experimental results validate the effectiveness of the proposed GA in selecting pickup nodes and arranging the route. Moreover, the results demonstrate the characteristics and utility of the SPDP.