Optimization Models for Harvest and Production Planning in Agri-Food Supply Chain: A Systematic Review

This paper provides a comprehensive review of the research done on optimization models that focus on harvest and production planning for food crops. Optimization models have been used extensively in providing insights to decision-makers on issues related to harvest and production planning in agri-food supply chains. First, we conduct an extensive literature review on previous survey articles to distinguish our research from others. Based on the previous reviews, a new classification scheme is developed to classify articles systematically. Harvest and production planning problems in agri-food supply chains are analyzed through three sections: problem scope, model characteristics, and modeling approach. Neglected problem topics and several promising research directions are presented to stimulate research interest on agri-food supply chains specifically planning of harvest and production.

[1]  Mohammad R. Gholamian,et al.  Integrated network design of wheat supply chain: A real case of Iran , 2017, Comput. Electron. Agric..

[2]  Marcus Poggi de Aragão,et al.  Harvest planning in the Brazilian sugar cane industry via mixed integer programming , 2013, Eur. J. Oper. Res..

[3]  A. Higgins,et al.  Scheduling of brand production and shipping within a sugar supply chain , 2006, J. Oper. Res. Soc..

[4]  Mogens Graf Plessen.  Coupling of Crop Assignment and Vehicle Routing for Harvest Planning in Agriculture , 2017, Artificial Intelligence in Agriculture.

[5]  Franco Basso,et al.  A multi-objective approach for supporting wine grape harvest operations , 2020, Comput. Ind. Eng..

[6]  Supachai Pathumnakul,et al.  Application of crop growth simulation and mathematical modeling to supply chain management in the Thai sugar industry. , 2009 .

[7]  P. C. Marchal,et al.  Stochastic season-wide optimal production planning of virgin olive oil , 2018 .

[8]  R. Muneepeerakul,et al.  Modeling postharvest loss and water and energy use in Florida tomato operations , 2019, Postharvest Biology and Technology.

[9]  Reza Tavakkoli-Moghaddam,et al.  A Benders’ decomposition algorithm for optimizing distribution of perishable products considering postharvest biological behavior in agri-food supply chain: a case study of tomato , 2017, Central Eur. J. Oper. Res..

[10]  R. Akkerman,et al.  An optimization approach for managing fresh food quality throughout the supply chain , 2011 .

[11]  Marcela Cecilia González-Araya,et al.  Operational research models applied to the fresh fruit supply chain , 2016, Eur. J. Oper. Res..

[12]  Begoña Vitoriano,et al.  Two alternative models for farm management: Discrete versus continuous time horizon , 2003, Eur. J. Oper. Res..

[13]  Eleftherios Iakovou,et al.  Agrifood supply chain management: A comprehensive hierarchical decision-making framework and a critical taxonomy , 2014 .

[14]  Ruud H. Teunter,et al.  Crop-related harvesting and processing planning: a review , 2016 .

[15]  Supachai Pathumnakul,et al.  Harvest scheduling algorithm to equalize supplier benefits: A case study from the Thai sugar cane industry , 2015, Comput. Electron. Agric..

[16]  Hector Flores,et al.  A stochastic planning framework for the discovery of complementary, agricultural systems , 2020, Eur. J. Oper. Res..

[17]  Timothy J. Lowe,et al.  Decision Technologies for Agribusiness Problems: A Brief Review of Selected Literature and a Call for Research , 2004, Manuf. Serv. Oper. Manag..

[18]  O. Ahumada,et al.  Operational model for planning the harvest and distribution of perishable agricultural products , 2011 .

[19]  Juan-Carlos Ferrer,et al.  An optimization approach for scheduling wine grape harvest operations , 2008 .

[20]  J. Rene Villalobos,et al.  A modeling framework for the strategic design of local fresh-food systems , 2018 .

[21]  Mohsen Varsei,et al.  Sustainable Supply Chain Network Design: A Case of the Wine Industry in Australia , 2016 .

[22]  Reinaldo Morabito,et al.  Robust optimisation approach applied to the analysis of production / logistics and crop planning in the tomato processing industry , 2016 .

[23]  Ehsan Nikbakhsh,et al.  Field path planning using capacitated arc routing problem , 2020, Comput. Electron. Agric..

[24]  Jesus Villalobos,et al.  Use of MIP for planning temporary immigrant farm labor force , 2015 .

[25]  Zainuddin Abdul Manan,et al.  A multi-period model for optimal planning of an integrated, resource-efficient rice mill , 2013, Comput. Chem. Eng..

[26]  O. Ahumada,et al.  Tactical planning of the production and distribution of fresh agricultural products under uncertainty , 2012 .

[27]  Andrew Higgins,et al.  An integrated statistical and optimisation approach to increasing sugar production within a mill region , 2005 .

[28]  José Vicente Caixeta-Filho,et al.  Orange harvesting scheduling management: a case study , 2006, J. Oper. Res. Soc..

[29]  Turan Paksoy,et al.  Application of fuzzy optimization to a supply chain network design: A case study of an edible vegetable oils manufacturer , 2012 .

[30]  Reinaldo Morabito,et al.  Optimization approaches to support decision making in the production planning of a citrus company: A Brazilian case study , 2014 .

[31]  Eligius M. T. Hendrix,et al.  Design of a supply chain network for pea-based novel protein foods , 2005 .

[32]  F. Jia,et al.  Agri-food supply chain management: bibliometric and content analyses. , 2018 .

[33]  José Eugenio Leal,et al.  A deterministic mathematical model to support temporal and spatial decisions of the soybean supply chain , 2015 .

[34]  Burak Kazaz,et al.  Production Planning Under Yield and Demand Uncertainty with Yield-Dependent Cost and Price , 2004, Manuf. Serv. Oper. Manag..

[35]  M. M. E. Alemany,et al.  Mathematical modelling of the order-promising process for fruit supply chains considering the perishability and subtypes of products , 2017 .

[36]  Emad Roghanian,et al.  Addressing a set of meta-heuristics to solve a multi-objective model for closed-loop citrus supply chain considering CO2 emissions , 2019 .

[37]  Mohammad Mahdi Paydar,et al.  A bi-objective optimization for citrus closed-loop supply chain using Pareto-based algorithms , 2018, Appl. Soft Comput..

[38]  Sanjay Jharkharia,et al.  Agri‐fresh produce supply chain management: a state‐of‐the‐art literature review , 2013 .

[39]  Marta Susana Moreno,et al.  A bi-objective optimization model for tactical planning in the pome fruit industry supply chain , 2016, Comput. Electron. Agric..

[40]  Fernando Augusto Silva Marins,et al.  Addressing uncertainty in sugarcane harvest planning through a revised multi-choice goal programming model , 2015 .

[41]  M. M. E. Alemany,et al.  Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models , 2018, Int. J. Prod. Res..

[42]  Alysson M. Costa,et al.  Sustainable vegetable crop supply problem with perishable stocks , 2011, Ann. Oper. Res..

[43]  Reinaldo Morabito,et al.  A Goal Programming Model for Frozen Concentrated Orange Juice Production and Distribution Systems , 2001 .

[44]  Jacqueline M. Bloemhof,et al.  Integrating harvesting decisions in the design of agro-food supply chains , 2019, Eur. J. Oper. Res..

[45]  Seyyed-Mahdi Hosseini-Motlagh,et al.  A novel hybrid approach for synchronized development of sustainability and resiliency in the wheat network , 2020, Comput. Electron. Agric..

[46]  Burak Kazaz,et al.  The Impact of Yield-Dependent Trading Costs on Pricing and Production Planning Under Supply Uncertainty , 2011, Manuf. Serv. Oper. Manag..

[47]  Rosa G. González-Ramírez,et al.  Research directions in technology development to support real-time decisions of fresh produce logistics: A review and research agenda , 2019, Comput. Electron. Agric..

[48]  Jesus René Villalobos,et al.  Application of planning models in the agri-food supply chain: A review , 2009, Eur. J. Oper. Res..

[49]  Kazuko Morizawa,et al.  OPTIMAL COOPERATIVE HARVESTING PATTERNS OF AGRICULTURAL FRESH PRODUCTS IN CASE OF MULTIPLE FARMERS AND MULTIPLE MARKETS UNDER PERIODICAL FLOWERING , 2009 .

[50]  F. Barzinpour,et al.  Designing and planning a rice supply chain: a case study for Iran farmlands , 2020 .

[51]  Jacqueline M. Bloemhof,et al.  Sustainable agro-food supply chain design using two-stage hybrid multi-objective decision-making approach , 2018, Comput. Oper. Res..

[52]  Hans-Otto Günther,et al.  Supply optimization for the production of raw sugar , 2007 .

[53]  Sergio Maturana,et al.  A robust optimization approach to wine grape harvesting scheduling , 2010, Eur. J. Oper. Res..

[54]  M. O'Sullivan,et al.  Agribusiness supply chain risk management: A review of quantitative decision models , 2017, Omega.

[55]  Mauricio Varas,et al.  A MIP formulation and a heuristic solution approach for the bottling scheduling problem in the wine industry , 2017, Comput. Ind. Eng..

[56]  F.D. Mele,et al.  A novel rolling horizon strategy for the strategic planning of supply chains. Application to the sugar cane industry of Argentina , 2011, Comput. Chem. Eng..

[57]  Jing Li,et al.  The two-echelon multi-trip vehicle routing problem with dynamic satellites for crop harvesting and transportation , 2019, Appl. Soft Comput..

[58]  Francisco Pérez-Galarce,et al.  Optimization of the harvest planning in the olive oil production: A case study in Chile , 2017, Comput. Electron. Agric..

[59]  Ebrahim Teimoury,et al.  A scenario-based stochastic programming approach for designing and planning wheat supply chain (A case study) , 2020 .

[60]  A. J. Higgins,et al.  Improving harvesting and transport planning within a sugar value chain , 2006, J. Oper. Res. Soc..

[61]  C. N. Bezuidenhout,et al.  An optimisation-based seasonal sugarcane harvest scheduling decision support system for commercial growers in South Africa , 2012 .

[62]  Gunjan Soni,et al.  Agri-fresh food supply chain quality (AFSCQ): a literature review , 2017, Ind. Manag. Data Syst..

[63]  K. Govindan,et al.  A sustainable supply chain for organic, conventional agro-food products: The role of demand substitution, climate change and public health , 2018, Journal of Cleaner Production.

[64]  William Sarache,et al.  Multiobjective stochastic scheduling of upstream operations in a sustainable sugarcane supply chain , 2020, Journal of Cleaner Production.

[65]  Reinaldo Morabito,et al.  Production and logistics planning in the tomato processing industry: A conceptual scheme and mathematical model , 2016, Comput. Electron. Agric..

[66]  S. Jeric,et al.  MULTI-OBJECTIVE OPTIMIZATION FOR THE INTEGRATED SUPPLY AND PRODUCTION PLANNING IN OLIVE OIL INDUSTRY , 2019 .

[67]  J. Bloemhof-Ruwaard,et al.  Accounting for uncertainty in eco-efficient agri-food supply chains: A case study for mushroom production planning , 2019, Journal of Cleaner Production.

[68]  G.D.H. Claassen,et al.  Closing loops in agricultural supply chains using multi-objective optimization : A case study of an industrial mushroom supply chain , 2017 .

[69]  Angappa Gunasekaran,et al.  Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications , 2019 .

[70]  K. Jármai,et al.  Analysis and optimisation of an olive oil supply chain: a case from Turkey , 2019, International Journal of Sustainable Agricultural Management and Informatics.

[72]  M. Nematollahi,et al.  Past, present, and prospective themes of sustainable agricultural supply chains: A content analysis , 2020, Journal of Cleaner Production.

[73]  S. Cholette,et al.  The land-network problem: ecosystem carbon balance in planning sustainable agro-food supply chains , 2016 .

[74]  Wahyudi Sutopo,et al.  An Agri-Food Supply Chain Model to Enhance the Business Skills of Small-Scale Farmers Using Corporate Social Responsibility , 2012 .

[75]  Vikas Kumar,et al.  A multi-objective mixed-integer linear model for sustainable fruit closed-loop supply chain network , 2020, Management of Environmental Quality: An International Journal.

[76]  Yanfeng Ouyang,et al.  Robust grain supply chain design considering post-harvest loss and harvest timing equilibrium , 2016 .

[77]  Baris Tan,et al.  Agricultural planning of annual plants under demand, maturation, harvest, and yield risk , 2012, Eur. J. Oper. Res..

[78]  Marcela Cecilia González-Araya,et al.  Optimizing tactical harvest planning for multiple fruit orchards using a metaheuristic modeling approach , 2021, Eur. J. Oper. Res..

[79]  S. Rahimifard,et al.  Resilience in agri-food supply chains: a critical analysis of the literature and synthesis of a novel framework , 2018 .

[80]  Marcela C. González-Araya,et al.  Harvest Planning in Apple Orchards Using an Optimization Model , 2015 .

[81]  Wilbert E. Wilhelm,et al.  OR/MS decision support models for the specialty crops industry: a literature review , 2011, Ann. Oper. Res..

[82]  Mohammad Mahdi Paydar,et al.  Wheat sustainable supply chain network design with forecasted demand by simulation , 2020, Comput. Electron. Agric..

[83]  John J. Glen,et al.  Feature Article - Mathematical Models in Farm Planning: A Survey , 1987, Oper. Res..

[84]  A. M. Blanco,et al.  Supply Chain Tactical Optimization in the Fruit Industry , 2011 .

[85]  Reinaldo Morabito,et al.  Modeling and solving a sugarcane harvest front scheduling problem , 2019, International Journal of Production Economics.

[86]  Jean-Paul M. Arnaout,et al.  Optimization of quality and operational costs through improved scheduling of harvest operations , 2010, Int. Trans. Oper. Res..

[87]  Jesus René Villalobos,et al.  A tactical model for planning the production and distribution of fresh produce , 2011, Ann. Oper. Res..

[88]  Mohammad Mahdi Paydar,et al.  Designing and solving a bi-level model for rice supply chain using the evolutionary algorithms , 2019, Comput. Electron. Agric..

[89]  Catherine Azzaro-Pantel,et al.  A green supply chain network design framework for the processed food industry: Application to the orange juice agrofood cluster , 2017, Comput. Ind. Eng..

[90]  K. H. Widodo,et al.  A periodical flowering-harvesting model for delivering agricultural fresh products , 2006, Eur. J. Oper. Res..