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A Hybrid Bayesian BWM–Fuzzy MARCOS–Metaheuristic Framework for Sustainable Smart Locker Location in Last-Mile Urban Logistics
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Sajjad Mohseni Andargoli   , Abdollah Arasteh * , Ali Divsalar |
| Babol Noshirvani University of Technology , arasteh@nit.ac.ir |
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Abstract: (56 Views) |
The explosive growth of global e-commerce and the increasing complexity of last-mile logistics have made the strategic placement of smart lockers a critical concern in modern urban logistics systems. Conventional methods, which rely solely on Multi-Criteria Decision Making (MCDM) methods for obtaining solutions, suffer from several limitations when implemented in uncertain, significant, and multi-objective scenarios. This paper proposes a stochastic multi-objective optimisation model for the BWM, prioritising decision criteria, which is solved by combining a hybrid metaheuristic solution methodology. The proposed model optimizes both total cost and sustainability performance from economic, environmental, and social perspectives, as well as robustness to demand uncertainty. An empirical study using Babol City, Iran, is presented to test and demonstrate the proposed framework. Candidate locker location and demand areas were examined based on expert-elicited criteria weights, with the preparation of a multi-objective mixed-integer programming model. In order to alleviate the computation burden, a combined structure of NSGA-II and LNS (referred to as NSGA-II+LNS) was proposed, which outperforms classical evolutionary algorithms in terms of convergence into the Pareto frontier. Factual results indicate that factoring in economic affordability, accessibility, and environmental impact is key to optimal locker capacity design. Robust solutions under demand fluctuation can save up to 18% more on service reliability, providing strong deterministic answers. This article makes the following theoretical and practical contributions: (i) a novel sustainable-oriented, deterministic model for smart locker location is proposed; (ii) advanced metaheuristics are integrated with MCDM in urban logistics, whereas fewer studies have focused on integrating them; and (iii) policy implications are suggested not only to policymakers but also to logistics operators who want robust last-mile delivery strategies..
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| Keywords: Smart lockers, Last-mile delivery, Stochastic multi-objective optimization, Best-Worst Method (BWM), Hybrid metaheuristics, Urban logistics |
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Type of Study: Applicable |
Subject:
Mathematical Modeling and Applications of OR
Received: 2025/10/5 | Accepted: 2025/10/26 | Published: 2025/11/3
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