Last-mile delivery: Optimal locker location under multinomial logit choice model

Yun Hui Lin, Yuan Wang, Dongdong He and Loo Hay Lee

Transportation Research Part E: Logistics and Transportation Review, 2020, vol. 142, issue C

Abstract: One innovative solution to the last-mile delivery problem is the self-service locker system. Motivated by a real case in Singapore, we consider a POP-Locker Alliance who operates a set of POP-stations and wishes to improve the last-mile delivery by opening new locker facilities. We propose a quantitative approach to determine the optimal locker location with the objective to maximize the overall service provided by the alliance. Customer’s choices regarding the use of facilities are explicitly considered. They are predicted by a multinomial logit model. We then formulate the location problem as a multi-ratio linear-fractional 0–1 program and provide two solution approaches. The first one is to reformulate the original problem as a mixed-integer linear program, which is further strengthened using conditional McCormick inequalities. This approach is an exact method, developed for small-scale problems. For large-scale problems, we propose an alternating algorithm, i.e., Quadratic Transform with Linear Alternating (QT-LA). The numerical experiment indicates that QT-LA is an efficient approach that yields high-quality solutions. Finally, we conducted a case study. The results highlighted the importance of considering the customers’ choices. Under different parameter values of the multinomial logit model, the decisions could be completely different. Therefore, the parameter value should be carefully estimated in advance.

Keywords: Locker location; Multinomial logit model; Last-mile delivery; Mixed-integer linear programming; Quadratic transform (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (25)

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DOI: 10.1016/j.tre.2020.102059

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