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. 2023 Jul 25;9(8):e18444.
doi: 10.1016/j.heliyon.2023.e18444. eCollection 2023 Aug.

Robust design of a logistics system using FePIA procedure and analysis of trade-offs between CO2 emissions and net present value

Andrés Polo Roa  1   2 , John Willmer Escobar  3 , María Paula Montoya  1
Affiliations

Robust design of a logistics system using FePIA procedure and analysis of trade-offs between CO2 emissions and net present value

Andrés Polo Roa et al. Heliyon. .

Abstract

The problems of flexible planning of the design of logistics systems for the collection of food products such as raw milk can result in a decrease in the performance of critical indicators for their performance. This paper proposes a new efficient methodology for robustly designing a first-mile logistics system for storing and refrigerating milk as a perishable product considering decisions related to open facilities and the flow of products, including sustainability indices. The proposed approach is modeled as a bi-objective problem by considering the minimization of greenhouse gas emissions (CO2) produced by milk transportation canteens and the maximization of the system configuration's net present value (NPV). We have analyzed and determined the most robust configuration for the first time and explained the robustness-NPV and robustness-CO2 relationships. The proposed mathematical model is solved by the Epsilon constraints method, and the robustness is calculated considering an extension of the FePIA methodology for multiobjective problems. A novel contribution is a balance in the possible future values generated by the company related to its cash flows and the generation of CO2 emissions when using a motorized transport frequently used in the shipment of raw milk considering a new important aspect such as the volume of product transported and the slope of the path between the production farm and the storage cooling tanks.

Keywords: Decision support system (DSS); FePIA; Supply chain; Sustainability.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
FePIA methodology.
Fig. 2
Fig. 2
Flowchart of the technical procedure for robustness analysis.
Fig. 3
Fig. 3
Pareto optimal curve for scenario π1.
Fig. 4
Fig. 4
Pareto optimal curve for scenario π2.
Fig. 5
Fig. 5
Pareto optimal curve for scenario π3.
Figure A1
Figure A1
Producer going up.
Figure A2
Figure A2
Producer going down.
Fig. 6
Fig. 6
Pareto optimal curve for scenario π4.
Fig. 7
Fig. 7
Configuration A for the supply chain system.
Fig. 8
Fig. 8
Configuration A for the supply chain system.
Fig. 9
Fig. 9
Configuration C for the supply chain system.
Fig. 10
Fig. 10
Configuration D for the supply chain system.
Fig. 11
Fig. 11
Configuration E for the supply chain system.
Fig. 12
Fig. 12
Configuration F for the supply chain system.
Graph 1
Graph 1
Obtained results for Γ1 4.4.2. CO2 emissions (Γ2).
Graph 2
Graph 2
Obtained results for Γ2.
Graph 3
Graph 3
Obtained results for Γ3 4.4.4. Walking distance (Γ4).
Graph 4
Graph 4
Obtained results for Γ4.
Graph 5
Graph 5
Obtained results for Γ5 4.5. Analysis of system performance characteristics (Φ).
Graph 6
Graph 6
Results for NPV.
Figure A3
Figure A3
Diagram for calculation of wind friction.
Graph 2
Graph 2
Diagram for calculation of acceleration.
See this image and copyright information in PMC

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