Optimization of Conventional and Green Vehicles Composition under Carbon Emission Cap
Round 1
Reviewer 1 Report
The manuscript is well organized and offers good information regarding the proposed algorithm. There are, however, some detailed comments and questions. The authors should consider and address in their revision, described below.
- The abstract should be more informative to present the findings of the work (including the results).
- The novelty of this work is unclear. In particular, the authors should clarify the novelty of this work.
- I find however the discussion poor. The readers would benefit from a more insightful discussion of the results and a clear statement about the main conclusions drawn from the research carried out.
- Please reconsider some paragraph which uses three same words… for example: “The first criterion is that in how many instances does the algorithm finds a better solution than the best know solution, ??? solution, found in the literature so far.”. Also, what means BKS (probably Best Known Solution?).
- Considering the aforementioned point, please add a table with the Abbreviations and Acronyms used in the paper.
- I strongly consider that there are many limitations to the proposed method. Please emphasize them in a subsection.
Overall, this is a good paper, if the authors consider the points above.
Author Response
Please see the attachment
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The authors propose an heuristic methodology in order to optimize the composition of conventional and green vehicles for a logistics distribution problem operating.
The article is interesting and well described. I only have few points to report as follows.
1) Usually it is not used the name "ant colony algorithm (ACA)" but "ant colony optimization (ACO)". This is more standard. I suggest to replace the name throughout the article.
2) The authors may extend their literature review by mentioning other recent important applications of ACO and VNS approaches such as e.g.
- Using pairwise precedences for solving the linear ordering problem, Applied Soft Computing, 2020
- A hybrid particle swarm optimization–variable neighborhood search algorithm for constrained shortest path problems, European Journal of Operational Research, 2017
- Improving variable neighborhood search to solve the traveling salesman problem, Applied Soft Computing, 2018
- A new precedence-based ant colony optimization for permutation problems, Asia-Pacific Conference on Simulated Evolution and Learning, 2017
- ....
3) In the experimental part, the authors should use a statistical test in order to compare the results among the different methodology tested. I suggest them to have a look at the following tutorial in order to choose the most suitable test for their experiment.
- A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms, Swarm and Evolutionary Computation, 2011
Author Response
Please see the attachment
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
The reviewer has no further comments, the authors have satisfactorily addressed most of my comments.
