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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. [ABSTRACT FROM AUTHOR]

These two-part paper series aim to optimize the rates of inspection-based maintenance or routine-test on power system equipment. Part I introduced a novel probabilistic model using Markov chains for the inspection-based maintenance and derived the relationships between the transition rates. Part II demonstrates how the proposed method can effectively address budget and data availability constraints. It also presents the derived relationships between the optimal preventive maintenance rate and risk indices. The results presented in this paper are based on an industrial project conducted to optimize the preventive maintenance period of high-voltage equipment in Iran. Additionally, this companion paper provides practical insights, including implementation remarks, and a comprehensive dataset for failure and defect analysis, which proves useful for future research and applications. • A case study on a real sub-transmission substation for the proposed model. • Derived relations between the optimal preventive maintenance rate and risk indices. • Analysis of the simultaneity in the inspection of series components. • How to overcome data and budget limitations by the proposed sensitivity analysis. • Practically, how to use the available data to optimize the inspection rate. [ABSTRACT FROM AUTHOR]