An Intelligent Waste Management Application Using IoT and a Genetic Algorithm–Fuzzy Inference System

Round 1

Reviewer 1 Report

The article discusses waste management that requires various IoT components to help, such as RFID and sensors. The novelty of the article is to develop an intelligent waste management model for smart cities using a hybrid mechanism using Fuzzy logic. The article uses the Mamdani model,which serves to evaluate waste management. The proposed model uses sensors to collect important information, where Fuzzy logic turns raw data into variables and FIS is trained to determine the likelihood that a smart container is almost approaching full.

This paper uses a genetic algorithm. The main problem in the traditional genetic algorithm is during the execution of the algorithm; There is a possibility of significant gene loss. This problem can be overcome by integrating Fuzzy logic with a genetic algorithm to achieve important genes.

The article also discloses the use of low-cost small-sized sensors in the system, which ensure the reproducibility of this solution. The Proteus simulator is used for experiments, and satisfactory results are obtained. Overall accuracy, accuracy and memorization of 95.44%, 96.68% and 93.96% are obtained in the proposed model.  The article provides a classification of items of recycling of raw materials.

The results obtained in this study are superior to other state-of-the-art studies that employed the same datasets.

 

The suggestions:

1.      No risk assessment was carried out in case of fuzzy operation of the system (in the state of emergency);

2.      The cloud computing system does not provide functional reliability of the city's infrastructure (stability of energy supply, transport, communication channels, telecommunications);

3.      Intelligent systems (cognitive, intelligent agents) in their ability to make decisions approach a certain level of human intelligence. Smart systems are not able to analyze problem situations, to be whole-oriented to generate ideas for solving problems.

4.    Іn the literature there is no reference to scientific and applied monographs on the system of intellectual management with a hierarchical structure.

 

Considering the relevance of the work and its scientific novelty

Comments for author File: Comments.pdf

Author Response

Title:  “An Intelligent Waste Management Application using IoT and a Genetic Algorithm-Fuzzy Inference System”

Manuscript Reference Number:   applsci-2158147 

The authors would like to take this opportunity to thank the reviewers for the effort and expertise that they contribute to reviewing, without which it would be impossible to maintain the high standards of research. We have attached the necessary corrections in the revised work. Additionally, we have highlighted all the changes in YELLOW in the revised manuscript.

 

1. No risk assessment was carried out in case of fuzzy operation of the system (in a state of emergency);

 

Response: A new section 3.4 on Risk Assessment is added to the proposed model.

 

2. The cloud computing system does not provide functional reliability of the city's infrastructure (stability of energy supply, transport, communication channels, telecommunications);

Response: Thanks for the reviewer's suggestion. We will take this into consideration for enhancing the reliability such as stability of energy supply, transportation, communication channels and telecommunication in further study. Presently, this work focuses on using the proposed GA-FIS model for implementing a smart waste management system with minimal human intervention. Alert generation is performed by cloud computing to ensure that if the bin level is more than half full, necessary instruction is sent to the client to empty the bin. This implementation provides functional reliability of the city’s infrastructure with regard to the security of the system as only authorized users can log in and utilize the system.

3. Intelligent systems (cognitive, intelligent agents) in their ability to make decisions approach a certain level of human intelligence. Smart systems are not able to analyze problem situations, to be whole-oriented to generate ideas for solving problems.

Response:  Thanks for the reviewer's suggestion. Yes, we agree. An intelligent smart waste management system is built by integrating IoT with GA-FIS to overcome the limitations of the normal smart system so as to reach cognitive intelligence. We tried to enhance the accuracy by 5% in comparison to the existing smart garbage systems shown in table 11.

4. In the literature there is no reference to scientific and applied monographs on the system of intellectual management with a hierarchical structure.

Response: Thanks for your feedback based on this we have elaborated our literature survey and included a few papers which speak about the implementation of intelligent-based management systems in the different hierarchical levels of governance. The following literature is detailed and cited in the literature section.

• Wang, C., Qin, J., Qu, C., Ran, X., Liu, C., & Chen, B. (2021). A smart municipal waste management system based on deep-learning and Internet of Things. Waste Management, 135, 20-29.
• Sharma, H. B., Vanapalli, K. R., Samal, B., Cheela, V. S., Dubey, B. K., & Bhattacharya, J. (2021). Circular economy approach in solid waste management system to achieve UN-SDGs: Solutions for post-COVID recovery. Science of The Total Environment, 800, 149605.
• Marques, Patric, Diogo Manfroi, Eduardo Deitos, Jonatan Cegoni, Rodrigo Castilhos, Juergen Rochol, Edison Pignaton, and Rafael Kunst. "An IoT-based smart cities infrastructure architecture applied to a waste management scenario." Ad Hoc Networks87 (2019): 200-208.

 

Reviewer 2 Report

The work is dedicated to the development of an intelligent waste management application using an IoT application for smart cities. Waste management is one issue which requires various IoT components for assistance such as RFIDs and sensors.An efficient and innovative waste collection is required to minimize the investment,
operational and expenditure costs. In this paper, the novel idea is to
develop an intelligent waste management model for smart cities using a hybrid
GA-Fuzzy Inference Engine. 

To select the development of an intelligent waste management application, the authors analyzed more than 40 publications. And as a result, they proposed their own method of filling containers with waste and sorting them.

The novelty of the article is to develop an intelligent waste management model for smart cities using a hybrid mechanism of Fuzzy GA inference.  Most of this, the authors compare their developed model with existing models . This developed model is improved due to the correctness and durability, which minimizes errors that may occur due to different working conditions.

The proposed model uses sensors to collect important information, where fuzzy logic turns raw data into variables and FIS is trained to determine the likelihood that a smart container is almost approaching full. Classification of recyclable items is also performed and accuracy isdetermined for every item resulting in minimization of resource waste. The cost of manual interpretation is minimized in the intelligent smart waste
management system in comparison to the traditional approach, which is shown
in the experiments.

The main problem of the article is solved - the creation of intelligent situational waste management in storage tanks based on the integration of methods of fuzzy logic and genetic algorithms.

 

The results obtained in this study are superior to other state-of-the-art studies that employed the same datasets.

 

The suggestions:

1.      The teaching of the material is heterogeneous: mixed system, scientific, engineering and hardware;

2.      The use of the considered method depending on the volume of waste (small, medium, large city) and the impact on the environment in case of an emergency is not justified

3.      Smart city and smart tank correctly called the intelligent situational control system;

4.      The literature does not provide references to basic books on artificial intelligence and intelligent control.

 

Considering the relevance of the work and its scientific novelty

Comments for author File: Comments.pdf

Author Response

Title:  “An Intelligent Waste Management Application using IoT and a Genetic Algorithm-Fuzzy Inference System”

Manuscript Reference Number:   applsci-2158147 

The authors would like to take this opportunity to thank the reviewers for the effort and expertise that they contribute to reviewing, without which it would be impossible to maintain the high standards of research. We have attached the necessary corrections in the revised work. Additionally, we have highlighted all the changes in YELLOW in the revised manuscript.

Reviewer 1:

1. The teaching of the material is heterogeneous: mixed system, scientific, engineering and hardware;

Response:

                  Thanks for the reviewer's suggestions, as rightly mentioned the system we develop is heterogeneous because the front-end hardware design involves sensors which capture the signal based on the type and quantity of waste collected, later a software-based intelligent system building is made to classify the waste with accuracy followed by wireless data communication network for instantaneously transferring the information to concerned authorities for initiating the action. This is a multi-domain system building, and the proposed work is to make this more efficient and accurate.  

 

2. The use of the considered method depending on the volume of waste (small, medium, large city) and the impact on the environment in case of an emergency is not justified

Response: A new section 3.4 on Risk Assessment is added to the proposed model

3. Smart city and smart tank correctly called the intelligent situational control system;

Response: Yes this work plays an important role in building smart and environment-friendly cities by appropriately deploying this model it helps to identify and recycle the waste, segregate the carcinogenic waste and destroy them and greatly helps in hygienic green environment building and thereby improve the circular economy of the nation.

This is added in the Introduction section

4. The literature does not provide references to basic books on artificial intelligence and intelligent control.

Response: References to basic books on Artificial Intelligence and Intelligent Control are added and detailed in the literature section.

Reviewer 3 Report

The authors observed a topic of intelligent waste management system based on integrated IoT and GA-fuzzy model. The paper has a low level of originality and significance of content. The English writing style, problem and model descriptions should also be improved. The detailed remarks are given in the following. I hope that these comments can help authors to improve their research.

English writing style should be improved (some not all remarks are given below):

• Line 19 “The proposed model uses sensors to collect vital information where fuzzy logic converts the raw data into variable to and FIS is trained to determine the probability that the smart bin is nearly full.”
• Line 188 “The ultrasonic sensor will be placed on the inner lid”, you should not write in the future tense. And after this, the authors wrote that the data will be sent ….
• The entire paragraph from line 231 is not understandable. What are you trying to describe here? Please rewrite it.

At line 2 authors claim the following “The primary issue in the traditional genetic algorithm is during the execution of the algorithm; there is a possibility of essential gene loss.”. According to what research is this based? On what essential loss are you referring?

The introduction segment should include an additional and more general description of waste management and IoT, as well as GA and Fuzzy concepts

Regarding the contributions of the submission (line 63): image classification, monitoring of waste in real-time and reuse of recyclables cannot be a new contribution because it is being used intensely for some time. Additionally, comparison with other models cannot be classified as a contribution. And finally, the integrated IoT with a fuzzy concept is not a novel approach to waste management (e.g. https://www.hindawi.com/journals/sp/2020/6613263/). Please elaborate on this. Authors should add research papers that observed IoT-fuzzy-waste management in the literature overview and define what is the contribution of the submission regarding existing research. Table 1. Should include important segments relevant to your research: e.g. sensor type (it is more important than focus on the communication technology), optimization technique or used models, waste type.

Based on the description of section 3.1 authors observe already developed technology not a technology in the research and development phase, where Arduino board has the implementation of the main submission contribution (first bullet of the contributions claimed by the authors), line 213 “The inclusion of a fuzzy inference with GA implementation on the Arduino board …”. Please elaborate on this issue.

Line 250: “The ultrasonic sensor keeps track of the garbage level. If the bin level is full, the information is sent to cloud for an alert generation which allows the client to empty the bin.”. Why do you wait for a bin to be full in order to send the information that someone should come and empty it? This collection cannot be instantaneous, some time will pass until someone comes to empty the bin and you will have waste overfilling and potential sanitary issues in the surrounding areas. 

Please include in section 3.2 the visual interpretation of a GA population member (chromosome), together with crossover and mutation operators.

Why do you need fuzzy rules to determine how much waste is in the bin? Modern sensors can pinpoint the level of waste in a bin. Please elaborate.

Line 575 of the Conclusion section: “Performance analysis on other smart bin loads is done to compare traditional GA with proposed GA-FIS, and it is evident that better fitness evolution results and reduced costs.” Why is this happening, you need to make a remark on the reasons which make these results.

Author Response

Response to Reviewer Comments

 

Title:  “An Intelligent Waste Management Application using IoT and a Genetic Algorithm-Fuzzy Inference System”

Manuscript Reference Number:   applsci-2158147 

The authors would like to take this opportunity to thank the reviewers for the effort and expertise that they contribute to reviewing, without which it would be impossible to maintain the high standards of research. We have attached the necessary corrections in the revised work. Additionally, we have highlighted all the changes in YELLOW in the revised manuscript.

The authors observed a topic of intelligent waste management systems based on integrated IoT and GA-fuzzy models. The paper has a low level of originality and significance of content. The English writing style, problem and model descriptions should also be improved. The detailed remarks are given in the following. I hope that these comments can help authors to improve their research.

English writing style should be improved (some not all remarks are given below):

• Line 19 “The proposed model uses sensors to collect vital information where fuzzy logic converts the raw data into variable and FIS is trained to determine the probability that the smart bin is nearly full.”
• Line 188 “The ultrasonic sensor will be placed on the inner lid”, you should not write in the future tense. And after this, the authors wrote that the data will be sent ….

 

Response: Updated the tense to be past tense in the entire paper.

• The entire paragraph from line 231 is not understandable. What are you trying to describe here? Please rewrite it.
• In line, 2 authors claim the following “The primary issue in the traditional genetic algorithm is during the execution of the algorithm; there is a possibility of essential gene loss.” According to what research is this based? On what essential loss are you referring?

 

Response:

 

In this work the essential gene loss refers to information relevant to the location, details regarding data of waste filling etc, these broken piece of information may lead to efficiency loss.

 

• The introduction segment should include an additional and more general description of waste management and IoT, as well as GA and Fuzzy concepts

Response:  The introduction segment is updated with detailed information about waste management, IoT, GA and fuzzy concepts.

• Regarding the contributions of the submission (line 63): image classification, monitoring of waste in real-time and reuse of recyclables cannot be a new contribution because it is being used intensely for some time. Additionally, comparison with other models cannot be classified as a contribution. And finally, the integrated IoT with a fuzzy concept is not a novel approach to waste management (e.g. https://www.hindawi.com/journals/sp/2020/6613263/). Please elaborate on this. Authors should add research papers that observed IoT-fuzzy-waste management in the literature overview and define what is the contribution of the submission regarding existing research.

 

Response: Yes it is true that there are few literatures which try to address solid waste management using IoT and Genetic algorithms but this work tries to compare the efficiency of those algorithms and the proposed algorithm proves to be more efficient in addition, this tries to address the problem of waste segregation that could be Reused, Recycled and could be used for generating the energy this helps a lot in achieving the sustainable development goals of the nation and also it tries to improve the economic and sanitary condition of a nation, in this context this research is unique [24]. More papers are added in the literature section including the paper given in the comment.

 

 

Table 1. Should include important segments relevant to your research: e.g. sensor type (it is more important than focus on the communication technology), optimization technique or used models, and waste type.

 

Response: Table 1 is updated with three more columns containing sensor type, models used and waste type.

 

 

Based on the description of section 3.1 authors observe already developed technology not a technology in the research and development phase, where Arduino board has the implementation of the main submission contribution (first bullet of the contributions claimed by the authors), line 213 “The inclusion of a fuzzy inference with GA implementation on the Arduino board …”. Please elaborate on this issue.

 

Response:  The GA rules can be incorporated into the system design by downloading those rules into the Arduino board which helps in the hardware setup for improvised decision-making in the identification and segregation of waste

 

Line 250: “The ultrasonic sensor keeps track of the garbage level. If the bin level is full, the information is sent to the cloud for an alert generation which allows the client to empty the bin.”. Why do you wait for a bin to be full in order to send the information that someone should come and empty it? This collection cannot be instantaneous, some time will pass until someone comes to empty the bin and you will have waste overfilling and potential sanitary issues in the surrounding areas.

 

Ans: The reviewer’s concern is well understood, actually the sanitation of a location is taken care of by the Municipal waste management system. This proposed work makes this system still smarter through the use of technology in terms of garbage collection, segregation, and indication to the concerned authorities (Municipal authorities are referred to as clients). In addition, this system provides control at the administrator end to provide a warning signal when the garbage reaches 60/70/80/90 per cent of the trash box, thereby it will definitely avoid the use of sanitary issues.

This is added in section 3.1 of the proposed model

 

Please include in section 3.2 the visual interpretation of a GA population member (chromosome), together with crossover and mutation operators.

Response:  Visual interpretation of GA operations like the crossover, exchanging genes, new offspring and mutation is represented in figure 5.

 

 

Why do you need fuzzy rules to determine how much waste is in the bin? Modern sensors can pinpoint the level of waste in a bin. Please elaborate.

Response:

 The fuzzy rules are set not only used to indicate the level of waste but also it speaks about the type of waste for segregation, they also provide the intelligence of what type of waste this bin has, whether the waste is reusable, recyclable , organic, e-waste etc

 

This is added in section 3.3 in the manuscript.

 

Line 575 of the Conclusion section: “Performance analysis on other smart bin loads is done to compare traditional GA with proposed GA-FIS, and it is evident that better fitness evolution results and reduced costs.” Why is this happening, you need to make a remark on the reasons which make these results.

Response:

The proposed algorithm performs better for multiple reasons starting from the collection, segregation and reuse, and recycling of waste by this really improvise the circular economy of the nation and also it helps to improve the environment and sub sequentially leads to the good sanitary condition of a nation.

This is added in the conclusion section.

 

Reviewer 4 Report

1.The authors should incorporate a flow chart of the methodology of the overall study in the introduction section for further clearance of objective

2. The literature review cited is very limited. The scope of the research is very vast. 

3. Most of the equations are not numbered and those which are numbered are not mentioned in the text. Please check this.

4. References are not cited properly. Remove all the lump references and elaborate on the details of each work separately. 

5. Please check references in lines 47-54. after 14 directly 42 is cited. 

6. Overall formatting and english and preposition require severe attention. 

Author Response

1. The authors should incorporate a flow chart of the methodology of the overall study in the introduction section for further clearance of objective

Response: A flow Chart is added in the introduction section.

2. The literature review cited is very limited. The scope of the research is very vast. 

Response: We have added few more research papers to solve this issue. Recent papers related to the proposed work are added in the literature section.

1. Most of the equations are not numbered and those which are numbered are not mentioned in the text. Please check this.

 

Response: All equations are numbered.

 

 

2. References are not cited properly. Remove all the lump references and elaborate on the details of each work separately. 

Response: All references are cited and lump references are removed and each work is cited

separately.

3. Please check the references in lines 47-54. after 14 directly 42 is cited. 

Response: References are cited in sequential order.

6. Overall formatting and English and preposition require severe attention. 

Response:  Based on this feedback a thorough revision of this article is made for a complete English language check.

 

Round 2

Reviewer 3 Report

The authors failed to provide adequate answers to some comments from the previous review round. In general, the new submission has the same main issues. The detailed remarks are given in the following. I hope that these comments can help authors to improve their research.

The following remark from the previous review round was not considered or answered by the authors (the text is not changed nor explained in more detail):

• The entire paragraph from line 231 is not understandable. What are you trying to describe here? Please rewrite it.

The authors did not provide full answers to the following comments from the previous review round: 

• At line 2 authors claim the following “The primary issue in the traditional genetic algorithm is during the execution of the algorithm; there is a possibility of essential gene loss.”. According to what research is this based? On what essential loss are you referring?

The authors did add new text to the submission which maybe leads to not defining all abbreviations correctly. Authors should define all abbreviations at the place of first use (e.g. GA etc.). Please check this in the entire submission.

Regarding the authors’ statement “Additionally, we have highlighted all the changes in YELLOW in the revised manuscript.”, this is not the case. For example, contributions at the end of section 1. (from line 119) are not highlighted. Please highlight all changes in the submission.

The following authors’ response is not understandable and must be rewritten (due to the English writing style that must be better): “Response: Yes it is true that there are few literatures which try to address solid waste management using IoT and Genetic algorithms but this work tries to compare the efficiency of those algorithms and the proposed algorithm proves to be more efficient in addition, this tries to address the problem of waste segregation that could be Reused, Recycled and could be used for generating the energy this helps a lot in achieving the sustainable development goals of the nation and also it tries to improve the economic and sanitary condition of a nation, in this context this research is unique [24]. More papers are added in the literature section including the paper given in the comment.” Additionally, the authors did not reflect on all issues from that comment.

The new submission contributions are not adequate, either they are not innovative and groundbreaking or they just cannot be classified as a contribution. For example, how can “reuse of recyclable items helps minimize resource waste” be a contribution?). 

Regarding the authors’ response: “Response: The GA rules can be incorporated into the system design by downloading those rules into the Arduino board which helps in the hardware setup for improvised decision-making in the identification and segregation of waste”, what is the contribution of the GA rules that you want to incorporate compared to the already incorporated GA on the Arduino board?

The authors' response to the following comment from the previous review round is not adequate: “Please include in section 3.2 the visual interpretation of a GA population member (chromosome), together with crossover and mutation operators.”. Authors must give a visual interpretation of the actual GA approach, not a general concept. How do you represent your solution via chromosome in your GA approach etc?

The authors did not provide an adequate answer to the following comment from the previous review round (authors, in their response, gave results, not reasons why the GA-FIS is better performing than GA):  

• Conclusion section: “Performance analysis on other smart bin loads is done to compare traditional GA with proposed GA-FIS, and it is evident that better fitness evolution results and reduced costs.” Why is this happening, you need to make a remark on the reasons which make these results.

 

Author Response

Response to Reviewer Comments

 

Title:  “An Intelligent Waste Management Application using IoT and a Genetic Algorithm-Fuzzy Inference System”

Manuscript Reference Number:   applsci-2158147 

The authors would like to take this opportunity to thank the reviewers for the effort and expertise that they contribute to reviewing, without which it would be impossible to maintain the high standards of research. We have attached the necessary corrections in the revised work. We have highlighted all the changes in RED in the revised manuscript.

Reviewer Comments:

 

The authors failed to provide adequate answers to some comments from the previous review round. In general, the new submission has the same main issues. The detailed remarks are given in the following. I hope that these comments can help authors to improve their research.

The following remark from the previous review round was not considered or answered by the authors (the text is not changed nor explained in more detail):

• The entire paragraph from line 231 is not understandable. What are you trying to describe here? Please rewrite it.

Authors Response:  Thanks for the reviewers suggestions. The lines from 231 are rewritten for better understanding.

 

The authors did not provide full answers to the following comments from the previous review round: 

• At line 2 authors claim the following “The primary issue in the traditional genetic algorithm is during the execution of the algorithm; there is a possibility of essential gene loss.”. According to what research is this based? On what essential loss are you referring?

 

Authors Response: In this paper, the essential gene loss refer to information relevant to location, details regarding data of waste filling etc, these broken piece of information may lead to efficiency or accuracy loss. Hence, the proposed GA-FIS is able to overcome this loss by preserving the FIS interpretability. For example, the effectiveness in tuning the membership functions and rule consequences through FIS is analysed. This is detailed in the abstract section.

 

The authors did add new text to the submission which maybe leads to not defining all abbreviations correctly. Authors should define all abbreviations at the place of first use (e.g. GA etc.). Please check this in the entire submission.

Response: All abbreviations are expanded in the first occurrence.

Regarding the authors’ statement “Additionally, we have highlighted all the changes in YELLOW in the revised manuscript.”, this is not the case. For example, contributions at the end of section 1. (from line 119) are not highlighted. Please highlight all changes in the submission.

 

Authors Response: Thanks for the reviewers response. The contributions are highlighted.

 

The following authors’ response is not understandable and must be rewritten (due to the English writing style that must be better): “Response: Yes it is true that there are few literatures which try to address solid waste management using IoT and Genetic algorithms but this work tries to compare the efficiency of those algorithms and the proposed algorithm proves to be more efficient in addition, this tries to address the problem of waste segregation that could be Reused, Recycled and could be used for generating the energy this helps a lot in achieving the sustainable development goals of the nation and also it tries to improve the economic and sanitary condition of a nation, in this context this research is unique [24]. More papers are added in the literature section including the paper given in the comment.” Additionally, the authors did not reflect on all issues from that comment.

The new submission contributions are not adequate, either they are not innovative and groundbreaking or they just cannot be classified as a contribution. For example, how can “reuse of recyclable items helps minimize resource waste” be a contribution?). 

Authors Response: We agree with the review’s view that this is not completely a new idea but this work tries to contribute for developing a better waste management system then the existing with enhanced reliability, cost efficient and more accurate waste management system which could help us a lot in smart city development projects. According to Environmental Protection Agency (EPA) report 80% of the landfilling waste could be recycled, we in this proposed work segregate waste into recyclable and non recyclable and thereby it could improve the cyclic economy of the nation.

Regarding the authors’ response: “Response: The GA rules can be incorporated into the system design by downloading those rules into the Arduino board which helps in the hardware setup for improvised decision-making in the identification and segregation of waste”, what is the contribution of the GA rules that you want to incorporate compared to the already incorporated GA on the Arduino board?

Authors Response:

                               The GA rules are incorporated for better waste segregation. The parameters such as proximity of the vehicle to the dustbin zone and waste filling level in the container (i.e. 80% or 90%) will change according to the user requirements. Therefore, the application demands an update in the GA rules in comparison to the already in built GA rules and the new rules will be downloaded into the Arduino board and same will be reconfigured into the board when there is a necessity.

 

The authors' response to the following comment from the previous review round is not adequate: “Please include in section 3.2 the visual interpretation of a GA population member (chromosome), together with crossover and mutation operators.”. Authors must give a visual interpretation of the actual GA approach, not a general concept. How do you represent your solution via chromosome in your GA approach etc?

 

Authors Response:

We missed to add this detail in the previous version considering the manuscript length. We have detailed this in section 4.1 Experimental Analysis. Figures 7 and 8 represent the solution via chromosome in our GA approach.

The authors did not provide an adequate answer to the following comment from the previous review round (authors, in their response, gave results, not reasons why the GA-FIS is better performing than GA):  

Authors Response:

 GA-FIS is performing better than GA as the operators have a direct influence on GA convergence.  The GA-FIS uses the adaptive change of GA operators during the run of GA. Statistic methods are used for appraisal of affectivity of GA-FIS [60]. The GA-FIS learning and prediction times were 3 and 10 seconds respectively, while those times were 223 and 345 seconds for the GA. Therefore, in the proposed work GA-FIS performs better as it is widely suited for dynamic environment.

 

• Conclusion section: “Performance analysis on other smart bin loads is done to compare traditional GA with proposed GA-FIS, and it is evident that better fitness evolution results and reduced costs.” Why is this happening, you need to make a remark on the reasons which make these results.

Authors Response: Figures 22 to 25 show the fitness evolution graphs of GA-FIS with GA for various smart load bins of 1 to 4. These results show the efficiency of GA-FIS over GA. This is because the FIS controls the fuzziness of GA parameters. From the graphs, we can determine there is an 8% reduction in cost when compared to the GA-FIS with the traditional GA from the graphs. Thus, the results show there is a reduced cost due to better fitness evolution.

 

Reviewer 4 Report

Suuficent improvment has been made.

Author Response

The reviewer has informed that sufficient improvements have been made in the revision