The position of the agricultural sector as a driving force for economic growth and development in the
urban and rural structure is one of the issues that has always been the subject of expert opinion. A
considerable amount of perishable products especially in the food and agriculture is corrupted annually
due to the lack of an effective mechanism in the supply chain. This forces researchers to plan and design
mathematical models to improve this situation. One of the most important tools in this field is supply
chain network design, which the researchers are trying to improve in the current human society by
extending this tool for the agriculture sector. For this purpose, in this research, we will briefly review
some of the work done. Finally, research gaps are provided for future research.
In today’s world, one of the basic problems of mankind is supplying food needs, so
that food security and quality assurance have become important goals of governments. In
particular, agricultural production has received special attention in developing countries .
Crops are those agricultural products that have less than one year of planting and flowering
(end of life). In fact, their lifecycle lasts less than a year; most crops are stored for several
months and only a part of the crop is directly consumed after harvest; Therefore, most small
and large producers prefer to stock these relatively sensitive crops for several months to
provide fruit in early spring, as well as reasonable prices due to market demand; Therefore,
it is necessary to have suitable places for storing high volume of manufactured products
and having a schedule. Also, because most warehouses are traditional, so every year a large
volume of products made with great effort and expense, these warehouses suffer a severe
loss of quality . The agricultural supply chain today has played an important role in supply
chain issues because of its unique characteristics such as the importance of food quality,
supply, climate change and price changes . These products are categorized in terms of shelf
life into perishable and non-perishable (such as grain and nuts) and in terms of life cycle
into agricultural and horticultural products . In recent years, the importance of fresh fruit
has grown substantially with increasing demand from concerned consumers for a healthy
diet. This has made the quality and availability of fruit throughout the year a significant
issue . Only in the past ten years has the agri-food industry in general and the fresh fruit
sector been specifically recognized and discussed in the supply chain as a key concept for
competitiveness [6,7]. For the first time, Ahumada and Villalobos conducted a study of model
planning in the agricultural supply chain. They have presented their research overview of
articles available since 1985 focusing on various crops including perishable, non-perishable,
and most vegetables . Audsley  also did research with an operation research model in
the agricultural sector but limited to examining developments in the United Kingdom .
Furthermore, Zhang  presented an interesting version of mathematical models for the
crop industry including fruits, vegetables, grapes, ornamental plants, tree nuts, berries and
dried fruits . On the other hand, Shukla and Jharkharia provided a summary of the existing
literature from 1991 to 2011 on the production of fresh produce such as fruits, flowers and
The main feature of their paper is to focus on the articles studied in the field of
perishable, non-perishable and fresh produce. They also categorized the literature studied by geographical area and journal. To focus more on supply chain
features, Farahani et al.  provided examples of decisions made
in generic supply chains, while Tsolakis et al.  presented the
type of decision making in agricultural supply chains. The process
of this investigation continues, and more attention is being
paid to this issue by 2019. For example, over the past two years,
Cheraghalipour et al.  have done several important researches
in the field of citrus [3,14,15] and rice  supply chains, which
considering the high assumptions have led to the complexity of their
model and proximity to the real world. In their recently published
work , they attempt to optimize total costs of the chain, demand
responsiveness, and CO2 emissions reduction. They used a novel
multi-objective metaheuristic called tree growth algorithm [16,17]
to solve their model (Figure 1). Due to the large number of articles
in this field, some of the other articles are reported in Tables 1 &
2 [18-24]. On the other hands, Figure 2 is illustrated to realize the
research labelled in Table 2 [25-35].
Figure 1: Percentage of research in Table 1 that considers its assumptions.
Figure 2: Percentage of research in Table 2 that considers its assumptions.
Table 1: Classifying related work on agricultural supply chain in terms of decision levels and variables.
Table 2: Classifying related work on agricultural supply chain in terms of solution approach, network flow and data.
As is displayed in this Figure 2, metaheuristics approach
covers 41%, exact method covers about 40%, and simulation
aid about 19% of these researches [36-42]. Also, most of these
research (75%) consider case study to accumulate data for their
model parameters [43-46]. Besides, Table 2 shows that all of these
researches considered forward flows, while only two researches
considered reverse flows or closed-loop network. To summarize, it
can be mentioned that we have briefly reviewed the research until
2019 in the field of agricultural supply chains. After descripting the
main subject, we attempt to find the behavior of 32 researches in
terms of various assumptions such as decision levels, considered
variables, solution approach, network flows, and type of data. After
reviewing and summarizing, the following gaps were identified for
Due to the above-mentioned gaps, the future works can cover strategic level in their research formulation.
The future works can more emphasis to some variables such as multi-vehicle, CO2 emission, and planting crops.
They can consider reverse flows and closed-loop structure in their network design.
Based on the reported results, they can use metaheuristic algorithms for large size problems.
Cheraghalipour A, Paydar MM, Keshteli MH (2018) Applying a hybrid BWM-VIKOR approach to supplier selection: a case study in the Iranian agricultural implements industry. Int J Appl Decis Sci 11(3): 274-301.
Paydar MM, Cheraghalipour A, Keshteli MH (2018) A Bi-Objective stochastic mathematical model for agricultural supply chain network. In: Int Conf Supply Chain Logist Manag, World Academy of Science, Engineering and Technology, International Science Index, Industrial and Manufacturing Engineering, Dubai, p. 1545.
Cheraghalipour A, keshteli MH (2017) Tree Growth Algorithm (TGA ): An effective metaheuristic algorithm inspired by trees behavior. In: 13th Int Conf Ind Eng, Scientific Information Databases, Babolsar, Iran, 13: 1-8.
Professor, Chief Doctor, Director of Department of Pediatric Surgery, Associate Director of Department of Surgery, Doctoral Supervisor Tongji hospital, Tongji medical college, Huazhong University of Science and Technology