A two-phase metaheuristic approach for the parcel locker location problem: First select then merge

The rapid growth of e-commerce has created the need to introduce new ideas in order to improve Last-Mile Delivery (LMD) logistics, which is considered the most expensive and time-consuming part of the goods delivery process. Parcel lockers are an emerging alternative to home delivery that presents great advantages, not only for companies, but also for consumers. In this paper, we propose the first select then merge methodology, which is a two-stage procedure that uses metaheuristic algorithms for optimal locker selection and relocation to maximize the delivery company’s profit, taking into account revenue and facility cost. In the first stage, the Locker Location Problem under the Threshold Luce (LLPTL) model, to predict the probability of customers using the locker service, is solved by a binary genetic algorithm in order to find the best locations from a predefined set of parcel lockers. To improve the solution, in the second stage, the Blend Crossover (BLX) method is implemented to merge two selected lockers and relocate them to a new optimal position neighboring the previous locations. The results show that the proposed methodology can further improve the profit of the delivery company by finding a balance between the revenue and the cost of the facilities. In addition, this increased profit using parcel lockers directly impacts the decrease of large delivery fleets, leading to a more efficient route in terms of cost and environmental impact.