A novel two-echelon hierarchical location-allocation-routing optimization for green energy-efficient logistics systems

The present paper addresses a novel two-echelon multi-product Location-Allocation-Routing problem (LARP). It also considers the integration of issues such as disruption, environmental pollution, and energy-efficient vehicles as currently critical issues in a Supply Chain Network (SCN) that includes production plants, central warehouses, and retailers. The aim of this study is to minimize the total cost, which involves costs related to the establishment, shipment processes, environmental pollution, travelling, vehicle usage, and fuel consumption, in a way to cover the total demand of retailers. The problem is NP-hard; thus, to solve it approximately, we developed Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithms. The numerical analysis showed that the proposed algorithms yielded high-quality results in a short computational time where the average gaps of GWO and PSO against CPLEX are 0.78% and 0.9%, respectively. Then, a case study of a dairy factory in Iran is conducted to evaluate the applicability of the proposed methodology and find the optimal policy. Finally, a set of sensitivity analyses is carried out to suggest managerial insights and decision aids.

Automated summary

The present paper addresses a novel two-echelon multi-product Location-Allocation-Routing problem (LARP) in a Supply Chain Network (SCN). It aims to minimize the total cost and integrate issues such as disruption, environmental pollution, and energy-efficient vehicles. Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithms are developed to solve the NP-hard problem. The proposed algorithms yield high-quality results and are validated with a case study and sensitivity analyses.