Collaborative Target Search Algorithm for UAV Based on Chaotic Disturbance Pigeon-Inspired Optimization

Round 1

Reviewer 1 Report

The main idea of this paper is absolutely clear. The authors have enhanced the classical PIO method to their modification called "chaotic disturbance pigeon-inspired optimization". Their modification leads to a significantly better convergence, and can avoid local minima/maxima when searching the global extreme. However, I have significant suggestions to improve this paper, in my opinion. Here, they're my comments and suggestions to the authors' text:
— Generally, the state-of-the-art in lines 30 through 102 looks fine. However, I recommend citing more varied methods for multi-objective optimization algorithms – please see some my suggestions below, regarding the references.
— Line 112: all the symbols used in this line should be briefly explained. (Not only some of them.)
— Line 130: "Where" should not be indented, and should be written as "where" at the beginning of the line as usual. (This error occurs in many other parts of the paper.)
— Please double check whether all symbols used in (1) through (8) are defined in the text – I don't think so.
— Line 202: For the Bernoulli transformation, a citation is necessary. (Not all readers know it...)
— Lines 235 and 240: Again, there are wrong indentations of "Where" as already mentioned above.
— Algorithm 3: Check all the symbols in the algorithm, e.g., the commas in Step6 are written in a bad way.
— Table 1: References to the benchmark functions should be defined (in the reference list at the end).
— Table 3: Attention! There are some errors in the table – "e-" not followed by numbers, i.e., some exponents are missing.
— Figure 1: The pictures are too small, the numbers on the axes are difficult to read. The figure could be wider, and therefore more readable.
— The test functions (e.g., the Rosenbrock one) are selected correctly. Again, some references should be included where these functions can be found.
— Figure 2: Again, the pictures are of a bad quality, the numbers are difficult to read. Generally, the figures should be remade.
— Lines 383 and 384: Again, there are wrong comma symbols, like `.
— Experimental Results, line 388: I think 4 UAVs are too small... Is it possible to include a test with a greater number of UAVs?
— The conclusion is clearly written. For the References, I suggest more citations to the multi-objective optimization, e.g.:
  ——FAKHFAKH, M., SALLEM, A., BOUGHARIOU, M., BENNOUR, S., BRADAI, E., GADDOUR, E., LOULO,U M. Analogue circuit optimization through a hybrid approach. Intelligent Computational Optimization in Engineering, Studies in Computational Intelligence. Berlin (Germany): Springer, 2011, vol. 366, p. 297–327.
  ——SHORBAGY, M., MOUSA, A. A. A., FATHI, W. Hybrid Particle Swarm Algorithm for Multiobjective Optimization: Integrating Particle Swarm Optimization with Genetic Algorithms for Multiobjective Optimization. Saarbrücken (Germany): LAP (LambertAcademic Publishing), 2011.
  ——DOBES, J., MICHAL, J., BIOLKOVA, V. Multiobjective optimization for electronic circuit design in time and frequency domains. Radioengineering, 2013, vol. 22, no. 1, p. 136–152.
  ——HIRANO, H., YOSHIKAWA, T. A study on two-step search using global-best in PSO for multi-objective optimization problems. In Proceedings of the 6th International Conference on Soft Computing and Intelligent Systems/13th International Symposium on Advanced Intelligent Systems (SCIS/ISIS). Kobe (Japan), 2012.
etc.
Generally, I recommend the paper for publishing after some necessary improvements.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

General comments

The paper entitled “Collaborative Target Search Algorithm for UAV Based on Chaotic Disturbance Pigeon-inspired Optimization” treats about a topic of the highest interest in the operational research scope with application in UAV cooperative missions. The declared aim of the manuscript is to improve the Pigeon-inspired optimization method (PIO), a new kind of particle optimization which possesses interesting characteristics. Notwithstanding PIO method demonstrated to outperform other similar methods, it maintains some limitations that are inherent to heuristics. Substantially, they often get in stuck in local optima. To overcome that shortcoming, Authors introduced a perturbation system, the chaotic disturbance, whose aim is to improve convergence to the global optimum. Therefore, the treated topic falls under the journal scope without any doubt.

Concerning the manuscript, the typographical outline is satisfactory and makes the paper readable. The used language is nearly fluent apart some unclear sentence. Abstract is well written. Introduction introduces the reader into the treated topic in a very effective manner. Keywords are pertinent to paper content and appropriate. Materials and Methods are very well described. The References section is good with recent citations. Graphic representations are sufficient.

Entering in the very merit of the paper, the methodology presented is interesting. The results are truly intriguing proving the efficacy of the proposed method.

In conclusion, this reviewer deems that the manuscript could be considered for publication after minor changes.

Author Response

Please see the attachment.

Author Response File: Author Response.docx