Mathematical Programming Models for Fresh Fruit Supply Chain Optimization: A Review of the Literature and Emerging Trends

Comments/Questions from Reviewer 1

Answers

(p.2) It is necessary to add a source to describe the Table 1.

(p.4) It is necessary to add a source to describe the Figure 1.

(p.4) It is necessary to add a source to describe the Table 2.

(p.8) It is necessary to add a source to describe the Figure 2.

(p.8) It is necessary to add a source to describe the Table 3.

(p.15) It is necessary to add a source to describe the Figure 3a, 3b.

Thank you for your comments about the content and structure of our manuscript.

Thank you also for your remarks on the English language, typos and writing errors in our manuscript. We have checked all these issues and made necessary corrections to improve the manuscript quality.

In conclusions, in addition to the above, I would expect an expression of opinion and perspective of the authors on the issue of the paper. Finally, the authors of the article should pay more attention to the overall writing and clarity of their article, which should support the demonstration of their findings.

Thank you for the remark and suggestion to improve our manuscript. The conclusion section has been re-written accordingly.

(lines 551-662)

Comments/Questions from Reviewer 2

Answers

The keywords are too specific and do not help the visibility of the manuscript

Agreed. We have simplified them.

The intro must consider some background. You do not need to subdivide this section

We agree with the suggestion not to subdivide this section, but the background was already included. We deleted the subdivision.

- What is FAO? Describe him

We actually introduced the Nomenclature for all acronyms in the end of the manuscript. With your suggestion, this word FAO is well described in line 50.

In the first paragraph you use "Fruits and vegetables" twice in a row. Consider improving it

Thank you for your note. It is improved now.

Table 2. It is necessary to indicate all the models (there are 3 pages of the manuscript). What does this info give us? What are the important ones? How are they ordered?

Thank you for this comment. Tables 2 and 3 in the old version of manuscript were combined and modified with indication for each model.

This table gives a quick view and summary on some common FFSC models.

- Table 3. Describe the acronyms in the table at the bottom

It is done. Table 3 in this version is merged with Table 2.

- Why put figures 3a, 3b ... and not 3,4 ...?

They are all corrected accordingly. Thanks.

- What does "The models in the literature can be viewed from a robustness point of view" mean? What literature do you rely on?

The robustness we used here is in the meaning ‘their ability to cope with external and internal disruptions and disturbances’.

The article we relied on is the following, and it is now correctly referred.

Monostori, J. Supply chains robustness: Challenges and opportunities. Procedia CIRP 2018, 67, 110-115

https://www.sciencedirect.com/science/article/pii/S2212827117311277

- Work limitations?

This is a review paper and since there are many papers in the literature, we may have missed. We have tried to focus on some important papers with the view to give the reader an understanding of mathematical models for fresh fruit supply chain optimization.

Comments/Questions from Reviewer 3

Answers

This paper addresses the issue of optimizing fresh fruit supply chains. Unfortunately, the work contains only a cursory overview of optimization models present in the literature on the subject and the justification why it is an important topic, according to the authors.

The presented literature review is very broad but shallow at the same time. An in-depth description of the models could significantly increase the value of the publication

Thank you for your comments.

We have modified and improved the manuscript with some in-depth description.

There is also no clear indication of which of the cited models are, according to the authors, the most appropriate for modeling supply chains of fresh fruit.

As we mentioned in our conclusion, we need standardization to evaluate the outcomes of each model. So far, we cannot point out what model is the most appropriate as each model has its weak and strong points, as well as advantages vs disadvantages.

Comments/Questions from Reviewer 2

Answers

The work focuses on a review of the literature, but there is only 1 from 2020. How is it possible? Check the most current literature.

We have updated our manuscript with 10 more recent papers added as shown below:

1.          Cheraghalipour, A.; Paydar, M. M.; Hajiaghaei-Keshteli, M. Designing and solving a bi-level model for rice supply chain using the evolutionary algorithms. Computers and Electronics in Agriculture, 2019, 162, 651-668.

2.          Foong, S. Z.; Goh, C. K.; Supramaniam, C. V.; Ng, D. K. Input–output optimisation model for sustainable oil palm plantation development. Sustainable Production and Consumption, 2019, 17, 31-46.

3.          Gokarn, S.; Kuthambalayan, T. S. Creating sustainable fresh produce supply chains by managing uncertainties. Journal of Cleaner Production, 2019, 207, 908-919.

4.          Ji, Y.; Du, J.; Han, X.; Wu, X.; Huang, R.; Wang, S.; Liu, Z. A mixed integer robust programming model for two-echelon inventory routing problem of perishable products. Physica A: Statistical Mechanics and its Applications, 2020, 548, 124481.

5.          Varas, M.; Basso, F.; Maturana, S.; Osorio, D.; Pezoa, R. A multi-objective approach for supporting wine grape harvest operations. Computers & Industrial Engineering, 2020, 145, 106497.

6.          Alemany, M. M. E.; Esteso, A.; Ortiz, Á.; del Pino, M. Centralized and distributed optimization models for the multi-farmer crop planning problem under uncertainty: Application to a fresh tomato Argentinean supply chain case study. Computers & Industrial Engineering, 2021, 153, 107048.

7.          Gómez-Lagos, J. E.; González-Araya, M. C.; Soto-Silva, W. E.; Rivera-Moraga, M. M. Optimizing tactical harvest planning for multiple fruit orchards using a metaheuristic modeling approach. European Journal of Operational Research, 2021, 290(1), 297-312.

8.          Ktenioudaki, A.; O'Donnell, C. P.; Emond, J. P.; do Nascimento Nunes, M. C. Blueberry supply chain: Critical steps impacting fruit quality and application of a boosted regression tree model to predict weight loss. Postharvest Biology and Technology, 2021, 179, 111590.

9.          Lim, C. H.; Cheah, Z. H.; Lee, X. H.; How, B. S.; Ng, W. P. Q.; Ngan, S. L.; Lam, H. L. Harvesting and evacuation route optimisation model for fresh fruit bunch in the oil palm plantation site. Journal of Cleaner Production, 2021, 307, 127238.

10.       Trivedi, A.; Sohal, A.; Joshi, S.; Sharma, M. A two-stage optimization model for tactical planning in fresh fruit supply chains: A case study of Kullu, India. International Journal of Supply and Operations Management, 2021, 8(1), 18-28.

Besides, the statistical data shown in Table 1 is also updated, and Figure 1 is redrawn to be clearly visible.

A few paragraphs for ideas. There are very short paragraphs.

Some short paragraphs have been merged and others have been expanded.

Comments/Questions from Reviewer 3

Answers

I support my comments on the previous version.

I have not noticed any deepening of the descriptions of the models cited. The only significant improvement is the clearer Table 2.

Please note that we have expanded on the description of the relevant mathematical models. There is now a Section summary at the end of each section to give the reader an overview of the models discussed and their potential extensions.

One paragraph has been added to the beginning of Section 5. Conclusion and research perspectives for future models to discuss the reviewed modelling methods and their advantages/disadvantages/data requirements:

All models reviewed are appropriate for the specific context and problems that they deal with. Thus, there is no overall best model. However, of all papers reviewed, the following ones propose integrated models of the supply chain under:

•           deterministic conditions (Hamer, 1994 [22], Munhoz and Morabito [67])

•           stochastic contexts (Bezat-Jarzębowska and Rembisz [63], Ahumada et al. [57])

•           sustainability considerations (Foong et al. [77], Van Der Vorst et al. [46])

•           multi-objective optimization (Cittadini et al. [44], Soto-Silva et al. [75])

•           multi-stage and multi-echelon network (Darby-Dowman et al. [28], Trivedi et al. [85])

•           comprehensive case studies (Broekmeulen [26], Verdouw et al. [51])