Agric. Econ. - Czech, X:X | DOI: 10.17221/76/2025-AGRICECON

Optimisation of agricultural logistics: A systematic review of modelling techniques and economic potentialsReview

Nikolas Bublik ORCID...1, Sebastian Hess ORCID...1
1 Department of Agricultural Markets, University of Hohenheim, Stuttgart, Germany

Agricultural logistics face unique challenges such as seasonal demand fluctuations, perishability, and geographic dispersion. The paper systematically analyses 63 peer-reviewed articles from 2013 to 2025, focusing on key optimisation techniques, including multi-criteria decision-making (MCDM), vehicle routing problems (VRP), and path planning problems (PPP). The findings highlight how logistics optimisation can reduce operational costs, improve resource utilisation, and enhance supply chain resilience. Additionally, the study identifies gaps in inbound logistics research and emphasises the need for further integration of digital technologies. Future research should focus on comprehensive, technology-driven solutions to improve adaptability and transparency in agricultural supply chains. Key findings reveal that optimised logistics models can lead to cost reductions of up to 58%, emissions savings of over 60%, and significant improvements in delivery time, field efficiency, and customer satisfaction.

Keywords: agricultural supply chains; vehicle routing problem; decision making in agriculture; path planning problem

Received: February 20, 2025; Revised: December 1, 2025; Accepted: December 2, 2025; Prepublished online: April 14, 2026 

Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. Amiama C., Cascudo N., Carpente L., Cerdeira-Pena A. (2015): A decision tool for maize silage harvest operations. Biosystems Engineering, 134: 94-104. Go to original source...
    2. Andric Gusavac B., Stanojevic M., Cangalovic M. (2019): Optimal treatment of agricultural land - Special multi-depot vehicle routing problem. Agricultural Economics - Czech, 65: 569-578. Go to original source...
    3. Anokić A., Stanimirović Z., Davidović T., Stakić Đ. (2020): Variable neighborhood search based approaches to a vehicle scheduling problem in agriculture. International Transactions in Operational Research, 27: 26-56. Go to original source...
    4. Archetti C., Bianchessi N., Irnich S., Speranza M.G. (2014): Formulations for an inventory routing problem. International Transactions in Operational Research, 21: 353-374. Go to original source...
    5. Aryal J.P., Rahut D.B., Thapa G., Simtowe F. (2021): Mechanisation of small-scale farms in South Asia: Empirical evidence derived from farm households survey. Technology in Society, 65: 101591. Go to original source...
    6. Bakhtiari A., Navid H., Mehri J., Berruto R., Bochtis D.D. (2013): Operations planning for agricultural harvesters using ant colony optimization. Spanish Journal of Agricultural Research, 11: 652. Go to original source...
    7. Bochtis D.D., Sørensen C.G., Busato P., Berruto R. (2013): Benefits from optimal route planning based on B-patterns. Biosystems Engineering, 115: 389-395. Go to original source...
    8. Bonadio B., Huo Z., Levchenko A.A., Pandalai-Nayar N. (2021): Global supply chains in the pandemic. Journal of International Economics, 133: 103534. Go to original source... Go to PubMed...
    9. Bramer W.M., Giustini D., Kramer B.M.R. (2016): Comparing the coverage, recall, and precision of searches for 120 systematic reviews in Embase, MEDLINE, and Google Scholar: A prospective study. Systematic Reviews, 5: 39. Go to original source... Go to PubMed...
    10. Bunte S., Kliewer N. (2009) An overview on vehicle scheduling models. Public Transport, 1: 299-317. Go to original source...
    11. Chandra S., Ghosh D., Srivastava S.K. (2016): Outbound logistics management practices in the automotive industry: An emerging economy perspective. Decision, 43: 145-165. Go to original source...
    12. Chen S., Gan M., Tang Y. (2013): Analysis of predicting the diversity regional logistics demand based on SVR: The case of Sichuan in China. Applied Mathematics & Information Sciences, 7: 645-651. Go to original source...
    13. Chen L., Ma M., Sun L. (2019a): Heuristic swarm intelligent optimization algorithm for path planning of agricultural product logistics distribution. Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, 37: 4697-4703. Go to original source...
    14. Chen J., Gui P., Ding T., Na S., Zhou Y. (2019b): Optimization of transportation routing problem for fresh food by improved ant colony algorithm based on tabu search. Sustainability, 11: 6584. Go to original source...
    15. Christiaensen L., Rutledge Z., Taylor J.E. (2021): Viewpoint: The future of work in agri-food. Food Policy, 99: 101963. Go to original source... Go to PubMed...
    16. Conesa-Muñoz J., Pajares G., Ribeiro A. (2016): Mix-opt: A new route operator for optimal coverage path planning for a fleet in an agricultural environment. Expert Systems with Applications, 54: 364-378. Go to original source...
    17. da Costa Santos C.M., de Mattos Pimenta C.A., Nobre M.R.C. (2007): The PICO strategy for the research question construction and evidence search. Revista Latino-Americana de Enfermagem, 15: 508-511. Go to original source... Go to PubMed...
    18. Dantzig G.B., Ramser J.H. (1959): The truck dispatching problem. Management Science, 6: 80-91. Go to original source...
    19. Dantzig G.B., Fulkerson D.R. (2003): Minimizing the number of tankers to meet a fixed schedule. Stanford Business Books, Stanford, California
    20. Dantzig G. B., & Fulkerson D. R. (1954): Minimizing the number of carriers to meet a fixed schedule. Go to original source...
    21. Dong B., Duan M., Li Y. (2022): Exploration of Joint optimization and visualization of inventory transportation in agricultural logistics based on ant colony algorithm. Computational Intelligence and Neuroscience, 2022: 2041592. Go to original source... Go to PubMed...
    22. Erdoğan S., Miller-Hooks E. (2012): A green vehicle routing problem. Transportation Research Part E: Logistics and Transportation Review, 48: 100-114. Go to original source...
    23. European Commission (2020): Farm to Fork Strategy. Brussels, European Commission. Available at https://food.ec.europa.eu/horizontal-topics/farm-fork-strategy_en
    24. Fallahi A.E., Prins C., Wolfler Calvo R. (2008): A memetic algorithm and a tabu search for the multi-compartment vehicle routing problem. Computers & Operations Research, 35: 1725-1741. Go to original source...
    25. Farghali M., Osman A.I., Mohamed I.M.A., Chen Z., Chen L., Ihara I., Yap P.-S., Rooney D.W. (2023): Strategies to save energy in the context of the energy crisis: A review. Environmental Chemistry Letters, 21: 2003-2039. Go to original source... Go to PubMed...
    26. Gao T., Erokhin V., Arskiy A. (2019): Dynamic optimization of fuel and logistics costs as a tool in pursuing economic sustainability of a farm. Sustainability, 11: 5463. Go to original source...
    27. Gehanno J.-F., Rollin L., Darmoni S. (2013): Is the coverage of Google Scholar enough to be used alone for systematic reviews. BMC Medical Informatics and Decision Making, 13: 7. Go to original source... Go to PubMed...
    28. Gracia C., Velázquez-Martí B., Estornell J. (2014): An application of the vehicle routing problem to biomass transportation. Biosystems Engineering, 124: 40-52. Go to original source...
    29. Gu Z., Liu W., Ren Y., Hai L., Xue Y. (2023): An Improved path optimization method of logistics site selection for agricultural products. JESTR, 16: 44-51. Go to original source...
    30. Guitián de Frutos R.M., Casas-Méndez B. (2019): Routing problems in agricultural cooperatives: A model for optimization of transport vehicle logistics. IMA Journal of Management Mathematics, 30: 387-412. Go to original source...
    31. Gupta H., Kharub M., Shreshth K., Kumar A., Huisingh D., Kumar A. (2023): Evaluation of strategies to manage risks in smart, sustainable agri-logistics sector: A Bayesian-based group decision-making approach. Business Strategy and the Environment, 32: 4335-4359. Go to original source...
    32. Hameed I.A. (2014): Intelligent coverage path planning for agricultural robots and autonomous machines on three-dimensional terrain. Journal of Intelligent & Robotic Systems, 74: 965-983. Go to original source...
    33. He P., Li J. (2019): The two-echelon multi-trip vehicle routing problem with dynamic satellites for crop harvesting and transportation. Applied Soft Computing, 77: 387-398. Go to original source...
    34. Igwe A.N., Eyo-Udo N.L., Toromade A.S., Adewale T.T. (2024): Policy implications and economic incentives for sustainable supply chain practices in the food and FMCG Sectors. Comprehensive Research and Reviews Journal, 2: 23-36. Go to original source...
    35. Ismail A.H., Hartono N., Zeybek S., Caterino M., Jiang K. (2021): Combinatorial bees algorithm for vehicle routing problem. Macromolecular Symposia, 396: 2000284. Go to original source...
    36. Jensen T.A., Antille D.L., Tullberg J.N. (2025): Improving on-farm energy use efficiency by optimizing machinery operations and management: A review. Agricultural Research, 14: 15-33. Go to original source...
    37. Kandiller L., Eliiyi D.T., Taşar B. (2017): A multi-compartment vehicle routing problem for livestock feed distribution. In: Dörner K., Ljubic I., Pflug G., Tragler G. (eds): Operations Research Proceedings 2015. Vienna, Austria, Sept 1-4, 2015: 149-155. Go to original source...
    38. Kang J.-R., Chang M.-H. (2024): The Application of elite genetic algorithm in sustainable agricultural transportation. In: Proceedings of the 2024 International Conference on Information Technology, Data Science, and Optimization. Taipei, Taiwan, May 22-24, 2024: 6-11. Go to original source...
    39. Katiyar S., Khan R., Kumar S. (2021): Artificial bee colony algorithm for fresh food distribution without quality loss by delivery route optimization. Journal of Food Quality, 2021: 4881289. Go to original source...
    40. Keshav S. (2007): How to read a paper. SIGCOMM Computer Communication Review, 37: 83-84. Go to original source...
    41. Khajepour A., Sheikhmohammady M., Nikbakhsh E. (2020): Field path planning using capacitated arc routing problem. Computers and Electronics in Agriculture, 173: 105401. Go to original source...
    42. Kramar U., Topolšek D., Lipičnik M. (2015): How to define logistics in agriculture?
    43. Kumar A., Mangla S.K., Kumar P., Song M. (2021): Mitigate risks in perishable food supply chains: Learning from COVID-19. Technological Forecasting and Social Change, 166: 120643. Go to original source...
    44. Kumar P., Kumar Singh R. (2022): Strategic framework for developing resilience in Agri-Food Supply Chains during COVID 19 pandemic. International Journal of Logistics Research and Applications, 25: 1401-1424. Go to original source...
    45. Lahyani R., Coelho L.C., Khemakhem M., Laporte G., Semet F. (2015): A multi-compartment vehicle routing problem arising in the collection of olive oil in Tunisia. Omega, 51: 1-10. Go to original source...
    46. Laporte G., Osman I.H. (1995): Routing problems: A bibliography. Annals of Operations Ressearch, 61: 227-262. Go to original source...
    47. Liao L., Li J., Wu Y. (2013): Modeling and optimization of inventory-distribution routing problem for agriculture products supply chain. Discrete Dynamics in Nature and Society, 2013: 409869. Go to original source...
    48. Liu L., Wang H., Xing S. (2019) Optimization of distribution planning for agricultural products in logistics based on degree of maturity. Computers and Electronics in Agriculture 160: 1-7. Go to original source...
    49. Liu G., Hu J., Yang Y., Xia S., Lim M.K. (2020): Vehicle routing problem in cold Chain logistics: A joint distribution model with carbon trading mechanisms. Resources, Conservation and Recycling, 156: 104715. Go to original source...
    50. Lujak M., Sklar E., Semet F. (2021): Agriculture fleet vehicle routing: A decentralised and dynamic problem. AI Communications: The European Journal on Artificial Intelligence, 34: 55-71. Go to original source...
    51. Lummus R.R., Krumwiede D.W., Vokurka R.J. (2001): The relationship of logistics to supply chain management: Developing a common industry definition. Industrial Management & Data Systems, 101: 426-432. Go to original source...
    52. Mahmud N., Haque M.M. (2019): Solving multiple depot vehicle routing problem (MDVRP) using genetic algorithm. In: 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE). Cox'sBazar, Bangladesh, Feb 7-9, 2019: 1-6. Go to original source...
    53. Mai T., Shao S., Yun Z. (2019): The Path planning of agricultural AGV in potato ridge cultivation. Annals of Advanced Agricultural Sciences, 3: 21-30. Go to original source...
    54. Mamoudan M.M., Jafari A., Mohammadnazari Z., Nasiri M.M., Yazdani M. (2023): Hybrid machine learning-metaheuristic model for sustainable agri-food production and supply chain planning under water scarcity. Resources, Environment and Sustainability, 14: 100133. Go to original source...
    55. Mentzer J.T., DeWitt W., Keebler J.S., Min S., Nix N.W., Smith C.D., Zacharia Z.G. (2001): Defining supply chains management. Journal of Business Logistics, 22: 1-25. Go to original source...
    56. Miao H. (2024): Logistics distribution path optimization and application based on swarm intelligence optimization algorithm. In: Mezhuyev V., Becker Westphall C., Uden L., Wolfson O., Agaian S.S.: Intelligent Transportation and Smart Cities, Proceedings of the 1st International Conference (ICITSC 2024). Wuhan, China, March 7-8, 2024: 57-64.
    57. Mizik T., Nagy J., Molnár E.M., Maró Z.M. (2025): Challenges of employment in the agrifood sector of developing countries - A systematic literature review. Humanities and Social Sciences Communications, 12: 62. Go to original source...
    58. Muthukumaran S., Ganesan M., Dhanasekar J., Loganathan G.B. (2021): Path planning optimization for agricultural spraying robots using hybrid dragonfly - Cuckoo search algorithm. Alinteri Journal of Agriculture Sciencea, 36: 412-419. Go to original source...
    59. Olufemi-Phillips A.Q., Ofodile O.C., Toromade A.S., Igwe A.N,. Adewale T.T. (2024): Stabilizing food supply chains with Blockchain technology during periods of economic inflation. International Journal of Advanced Economics, 6: 612-651. Go to original source...
    60. Patidar R., Venkatesh B., Pratap S., Daultani Y. (2018): A sustainable vehicle routing problem for Indian agri-food supply chain network design. In: 2018 International Conference on Production and Operations Management Society (POMS). Peradeniya, Sri Lanka, Dec 14-16, 2018. Go to original source...
    61. Petersen K., Feldt R., Mujtaba S., Mattsson M. (2008): Systematic mapping studies in software engineering. In: Visaggio G., Baldassarre M.T., Linkman S., Turner M.: Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering (EASE). Italy, June 26-27, 2008: 68-77. Go to original source...
    62. Pratap S., Jauhar S.K., Paul S.K., Zhou F. (2022): Stochastic optimization approach for green routing and planning in perishable food production. Journal of Cleaner Production, 333: 130063. Go to original source...
    63. Qin G., Tao F., Li L. (2019:) A vehicle routing optimization problem for cold chain logistics considering customer satisfaction and carbon emissions. International Journal of Environmental Research and Public Health, 16: 576. Go to original source... Go to PubMed...
    64. Rahim M., Radzuan K., Nadarajan S., Bolaji B.H., Ramli M.F. (2024): Modelling and simulation of the single-period vehicle routing problem in the agriculture industry. JESA, 57: 1445-1451. Go to original source...
    65. Ren Q. (2022): The optimal route selection model of fresh agricultural products transportation based on bee colony algorithm. International Journal of Advanced Computer Science and Applications, 13: 489-499. Go to original source...
    66. Saitone T.L., Sexton R.J. (2017): Agri-food supply chain: Evolution and performance with conflicting consumer and societal demands. European Review of Agricultural Economics, 44: 634-657. Go to original source...
    67. Sánchez-Bravo P., Chambers V.E., Noguera-Artiaga L., Sendra E., Chambers I.V.E., Carbonell-Barrachina Á.A. (2021): Consumer understanding of sustainability concept in agricultural products. Food Quality and Preference, 89: 104136. Go to original source...
    68. Sethanan K., Neungmatcha W. (2016): Multi-objective particle swarm optimization for mechanical harvester route planning of sugarcane field operations. European Journal of Operational Research, 252: 969-984. Go to original source...
    69. Sethanan K., Pitakaso R. (2016): Differential evolution algorithms for scheduling raw milk transportation. Computers and Electronics in Agriculture, 121: 245-259. Go to original source...
    70. Seyyedhasani H., Dvorak J.S. (2017): Using the vehicle routing problem to reduce field completion times with multiple machines. Computers and Electronics in Agriculture, 134: 142-150. Go to original source...
    71. Seyyedhasani H., Dvorak J.S. (2018): Dynamic rerouting of a fleet of vehicles in agricultural operations through a dynamic multiple depot vehicle routing problem representation. Biosystems Engineering, 171: 63-77. Go to original source...
    72. Singh J., Gupta V. (2017a): A systematic review of text stemming techniques. Artificial Intelligence Review, 48: 157-217. Go to original source...
    73. Singh J., Gupta V. (2017b): Text Stemming: Approached, applications, and challenges. ACM Computing Surveys, 49: 45. Go to original source...
    74. Solomon M.M. (1987): Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations Research, 35: 254-265. Go to original source...
    75. Spekken M., de Bruin S. (2013): Optimized routing on agricultural fields by minimizing maneuvering and servicing time. Precision Agric, 14: 224-244. Go to original source...
    76. Sun M., Pang D. (2017): Vehicle routing optimisation algorithm for agricultural products logistics distribution. International Journal of Applied Decision Sciences, 10: 327-334. Go to original source...
    77. Sun F., Wang X., Zhang R. (2020): Task scheduling system for UAV operations in agricultural plant protection environment. Journal of Ambient Intelligence and Human Computing. Go to original source...
    78. Szabo Ľ., Richnák P., Gubová K. (2021): New dimension of logistics innovations development in agricultural enterprises in Slovakia. Agricultural Economics - Czech, 67: 136-143. Go to original source...
    79. Taherdoost H., Madanchian M. (2023): Multi-criteria decision making (MCDM) methods and concepts. Encyclopedia, 3: 77-87. Go to original source...
    80. Tang J., Liu K., Chen Q. (2013): Study on cold chain logistics of vehicle routing problem for agricultural products. In: Proceedings of 2013 IEEE International Conference on Service Operations and Logistics, and Informatics. Dongguan, P.R. China, July 28-30, 2013: 317-322. Go to original source...
    81. Theeraviriya C., Ruamboon K., Praseeratasang N. (2021): Solving the multi-level location routing problem considering the environmental impact using a hybrid metaheuristic. International Journal of Engineering Business Management, 13. Go to original source...
    82. Utamima A., Reiners T., Ansaripoor A. (2019a): Decision making for Farmers: A case study of agricultural routing planning. In: ACIS 2019 Proceedings. Perth, Australia, Dec 9-11, 2019: 789-799.
    83. Utamima A., Reiners T., Ansaripoor A.H. (2019b): Evolutionary estimation of distribution algorithm for agricultural routing planning in field logistics. Procedia Computer Science, 161: 560-567. Go to original source...
    84. Utamima A., Reiners T., Ansaripoor A. (2019c): Optimisation of agricultural routing planning in field logistics with evolutionary hybrid neighbourhood search. Biosystems Engineering, 184: 166-180. Go to original source...
    85. Utamima A., Reiners T., Ansaripoor A. (2020): Automation in agriculture: A case study of route planning using an evolutionary lovebird algorithm. In: Proceedings of the 2020 12th International Conference on Computer and Automation Engineering. Sydney, Australia, Feb 14-16, 2020: 13-17. Go to original source...
    86. Uyar A. (2009): Google stemming mechanisms. Journal of Information Science, 35: 499-514. Go to original source...
    87. Valente J., Del Cerro J., Barrientos A., Sanz D. (2013): Aerial coverage optimization in precision agriculture management: A musical harmony inspired approach. Computers and Electronics in Agriculture, 99: 153-159. Go to original source...
    88. Wang Y., Xie M. (2024): Analysis on path optimization of agricultural warehouse logistics handling robot based on potential field ant colony algorithm. INMATEH - Agricultural Engineering, 73: 784-795. Go to original source...
    89. Wu D., Wu C. (2021): TDGVRPSTW of Fresh agricultural products distribution: Considering both economic cost and environmental cost. Applied Sciences, 11: 10579. Go to original source...
    90. Wu D., Wu C. (2022): Research on the time-dependent split delivery green vehicle routing problem for fresh agricultural products with multiple time windows. Agriculture, 12: 793. Go to original source...
    91. Wu D., Zhu Z., Hu D., Mansour R.F. (2022): Optimizing fresh logistics distribution route based on improved ant colony algorithm. Computer, Materials & Continua, 73: 2079-2095. Go to original source...
    92. Wu D., Yan R., Jin H., Cai F. (2023a): An Adaptive nutcracker optimization approach for distribution of fresh agricultural products with dynamic demands. Agriculture, 13: 1430. Go to original source...
    93. Wu D., Li J., Cui J., Hu D. (2023b): Research on the time-dependent vehicle routing problem for fresh agricultural products based on customer value. Agriculture, 13: 681. Go to original source...
    94. Xiong H. (2021): Research on cold chain logistics distribution route based on ant colony optimization algorithm. Discrete Dynamics in Nature and Society, 2021: 6623563. Go to original source...
    95. Xu S. (2011): Tactics on the development of modern agricultural logistics in central China. Advanced Materials Research, 219-220: 366-369. Go to original source...
    96. Xu Y. (2024): Research on agricultural logistics distribution path planning considering uav endurance mileage limit. INMATEH - Agricultural Engineering, 73: 688-701. Go to original source...
    97. Yang W., Xu J., Li Y. (2017): Multi-variety fresh agricultural products distribution optimization based on an improved cuckoo search algorithm. In: Fei M., Ma S., Yue D., Peng C., Li K., Xue Y. (eds): International Conference on Life System Modeling and Simulation, LSMS 2017 and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017. Nanjing, P.R. China, Sept 22-24, 2017: 294-302. Go to original source...
    98. Yao Q., Zhu S., Li Y. (2022): Green vehicle-routing problem of fresh agricultural products considering carbon emission. International Journal of Environmental Research and Public Health, 19: 8675. Go to original source... Go to PubMed...
    99. Yazdani M., Torkayesh A.E., Chatterjee P., Fallahpour A., Montero-Simo M.J., Araque-Padilla R.A., Wong K.Y. (2022): A fuzzy group decision-making model to measure resiliency in a food supply chain: A case study in Spain. Socio-Economic Planning Sciences, 82: 101257. Go to original source...
    100. Yu K., Liu Y., Sharma A. (2021): Analyze the effectiveness of the algorithm for agricultural product delivery vehicle routing problem based on mathematical model. International Journal of Agricultural and Environmental Information Systems, 12: 26-38. Go to original source...
    101. Zavala-Alcívar A., Verdecho M.-J., Alfaro-Saiz J.-J. (2021): Resilient strategies and sustainability in agri-food supply chains in the face of high-risk events. In: Camarinha-Matos L.M., Afsarmanesh H., Ortiz A. (eds): Boosting Collaborative Networks 4.0: PRO-VE 2020. Valencia, Spain, Nov 23-25, 2020: 560-570. Go to original source...
    102. Zhang S., Lee C., Choy K.L., Ho W., Ip W.H. (2014): Design and development of a hybrid artificial bee colony algorithm for the environmental vehicle routing problem. Transportation Research Part D: Transport and Environment, 31: 85-99. Go to original source...
    103. Zhou L., Hou G., Rao W. (2024): Collaborative logistics for agricultural products of 'farmer + consumer integration purchase' under platform empowerment. Expert Systems with Applications, 255: 124521. Go to original source...

    This is an open access article distributed under the terms of the Attribution 4.0 International (CC BY 4.0.), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return