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Article
Peer-Review Record

Transportation Asset Management Decision Support Tools: Computational Complexity, Transparency, and Realism

by Babatunde Atolagbe 1 and Sue McNeil 1,2,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Submission received: 1 September 2023 / Revised: 6 October 2023 / Accepted: 8 October 2023 / Published: 11 October 2023

Round 1

Reviewer 1 Report

This is an interesting exploration reviewing into the TAMPs and trying to shed light on tool selection. The process was well documented. The major shortcoming is the lack of some thorough discussion of the analysis process. The authors are encouraged to somehow succinctly describe the tools/ algorithms evaluated by adding in the rigor necessary for the quantitative part of the paper. Otherwise, it was felt that the title is a bit misleading, as the contents did not do justice supporting the title. 

Author Response

See attached.

Author Response File: Author Response.pdf

Reviewer 2 Report

The paper presents an interesting research study that discusses complexity, transparency, and realism in the context of transportation asset management. Below are the reviewer's comments along with suggested improvements:

1. Ensure that tables in the paper are appropriately referenced within the text.

2. Consider expanding Table 1 to include all commonly used objectives in transportation asset management optimization, similar to the comprehensive listing of options for other attributes.

3. Address and correct the "Error! Reference source not found" messages on page 3, 6, and 8. 

4.  More comprehensive information is required for the Computational Complexity case study in section 3.2.1, particularly regarding the problem formulation. The extended computational time of 3 hours for a basic network with only 11 links is atypical. In practice, transportation asset management optimization problems, even in the context of road networks with hundreds of thousands of sections, often yield solutions within 1 day. 

5. Enhance the discussion of transparency on pages 9 and 10, as the current coverage is insufficient.

6. Incorporate recommendations regarding the preferred model or approach for addressing complexities and enhancing transparency in transportation asset management in the conclusion. This will provide actionable insights for readers.

 

Author Response

See attached.

Author Response File: Author Response.pdf

Reviewer 3 Report

The objective of this paper, and the four issues demonstrated in it, are quite well stated. Challenges in incorporating optimization techniques into transportation asset management, such as data collection and management and complexity and availability of transportation systems, including optimization, are noted.

There is a good review of transportation asset management plans. There could be more discussion of the acronyms discussed, and particular of the DCMAC acronym.

There is a quite good analysis of the content of plans and their use in optimization. The discussion with respect to computational complexity of the relatively straight forward case study and the role of local sensitivity analysis, is also quite clear.

The computational effort with respect to the case study of a simple hypothetical network is noted. It could be discussed in more depth. The importance of sensitivity analysis in simplifying the computational process is noted, as is the work by Zhou at al. (2002) in comparing the results of the DCMAC with a  range of different methods.

The discussion of the main issues identified in the paper, is comprehensive, The conclusions support the discussion in the paper.

There are some “Error! Reference source not found.” references when the authors refer to Tables 1, 2 and 3.

The English language in this paper is of quite good quality.

Author Response

See attached

Author Response File: Author Response.pdf

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