An Effective Metaheuristic Approach for Building Energy Optimization Problems

Round 1

Reviewer 1 Report

The manuscript: "An effective Metaheuristic Approach for Building Energy Optimization Problems" presents a relevant and current scientific issue for simulating and optimizing the energy systems of low-energy buildings. The manuscript is part of the issue of energy-saving construction and sustainable development in construction.

I believe that the manuscript can be admitted to the next stage of the proceedings, provided that the following comments are taken into account: 

1. The abstract of the manuscript should be supplemented with specific information regarding the most important results of the analyzes performed.

2. I believe that in order to improve the perception of the content presented in the manuscript, the graphic part of the presented results should be improved, e.g. by extending the comparative analysis of the thermal performance of the considered building components in the annual period.

3. The manuscript should be supplemented with information on the applicability range of the considered model, for various external climate conditions and other variables, such as the thermal capacity of buildings.

Author Response

The authors would like to thank the reviewer for the insightful and constructive feedback and comments. We have carefully addressed all comments and provided a point-by-point response in the attached file. We also highlighted all corresponding changes in the revised manuscript. We hope that the revised manuscripts meets the reviewer's satisfaction and the journal's standards.

Author Response File: Author Response.pdf

Reviewer 2 Report

There is the certain workload and the research idea is interesting. However, this study only proposed a method, which was simply verified a building.

The main problems must be solved as following?

1. In Fig. 1, why is there only one feedback to input parameters?

2. There is no quantitative conclusions

3. how to ensure the numerical precision and accuracy.

Author Response

The authors would like to thank the reviewer for the insightful and constructive feedback and comments. We have carefully addressed all comments and provided a point-by-point response in the attached file. We also highlighted all corresponding changes in the revised manuscript. We hope that the revised manuscripts meets the reviewer's satisfaction and the journal's standards.

Author Response File: Author Response.pdf

Reviewer 3 Report

This study provides an effective hybrid technique based on pelican optimization algorithm ( POA ) and single candidate optimizer ( SCO ). The proposed hybrid algorithm ( POSCO ) benefits from the robust local search ability and effective global search ability of single candidate methods. The research topic of this article is clear, logical, and in line with the scope of the journal. However, in order to improve academic quality and persuasiveness, it is recommended to make some improvements before being recommended for acceptance. The specific opinions are as follows :

 

1. In section 2, the author introduces the parameter selection method of POA algorithm, which is not clear enough. The author suggests that the parameter setting method and the exact theoretical basis should be introduced in detail to avoid the dependence on specific problems and application environment.

 

2. In the paper, the advantages and disadvantages of POSCO are not introduced because many swarm algorithms have been used for optimization such as GA(Vibration-based structural damage identification under varying temperature effects), MFO(Damage Identification of Bridge Structures Considering Temperature Variations-Based SVM and MFO), MH-PSO (Bayesian Damage Identification based on Autoregressive Model and MH-PSO) and WOA(Structural damage identification based on substructure method and improved whale optimization algorithm), please compare the optimization methods with POSCO if possible in the section of INTRODUCTION .

 

3 In the POA algorithm, the pelican population is represented by a population matrix that approximates the prey ( exploration phase ). If the objective function value is improved at this position, the new position of the pelican is accepted. In this type of update, also known as effective update, the algorithm cannot move to non-optimal areas. The parameter setting is more complicated. If the parameter setting is improper, it is easy to deviate from the high-quality solution. It is recommended that the author improve the parameter selection method.

 

4. In section 4, the author introduces the hybrid pelican and single candidate optimizer algorithm. The global optimal solution obtained by the pelican optimization algorithm is input into SCO. The single candidate optimizer is a local optimization method, and the starting point has a considerable influence on the output of the algorithm, which needs to select an excellent starting point. This not only has a high requirement for the global search accuracy of the pelican optimization algorithm, but also has a certain requirement for the stability of the algorithm. The reviewer recommends that the author verify this point.

 

5. In section 5, the author puts forward the objective function of minimizing building energy consumption. The reviewer thinks that the author 's explanation of the function 's construction principle is insufficient and suggests that the author supplement it.

 

6. In section 6, the author proves the stability of POSCO algorithm by comparing it with POA, PSO, FA, MVO, SSA and TSA in terms of average value and standard deviation. The reviewer believes that the POSCO algorithm is an algorithm that combines global search ability and local search ability. The traditional optimization algorithm must be at a disadvantage in global or local search ability. It is recommended to increase the global-local optimization algorithm as a comparison to enhance the persuasiveness of the algorithm.

Author Response

The authors would like to thank the reviewer for the insightful and constructive feedback and comments. We have carefully addressed all comments and provided a point-by-point response in the attached file. We also highlighted all corresponding changes in the revised manuscript. We hope that the revised manuscripts meets the reviewer's satisfaction and the journal's standards.

Author Response File: Author Response.pdf