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A Comprehensive Review on NSGA-II for Multi-Objective Combinatorial Optimization Problems
2021
IEEE Access
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This paper provides an extensive review of the popular multi-objective optimization algorithm NSGA-II for selected combinatorial optimization problems viz. assignment problem, allocation problem, travelling ...
It is identified that based on the manner in which NSGA-II has been implemented for solving the aforementioned group of problems, there can be three categories: Conventional NSGA-II, where the authors ...
The authors introduced a new permutation representation and evaluated three different algorithms, i.e., NSGA-II, SPEA-II, and IVF/NSGA-II, on real scenarios. ...
doi:10.1109/access.2021.3070634
fatcat:fci76lcuw5gdjb4wr6wfn7ruqi
Supplementary Material for A Survey of Decomposition-Based Evolutionary Multi-Objective Optimization: PART II—A Data Science Perspective
[article]
2024
Zenodo
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This is the supplementary material for the manuscript entitled: "A Survey of Decomposition-Based Evolutionary Multi-Objective Optimization: PART II—A Data Science Perspective" submitted to IEEE. ...
T74 NSGA-II and Its Variants in Real-world Multi-Objective Optimization. ...
Emphasis is placed on adapting NSGA-II to handle complex, real-world scenarios characterized by interval objectives, set-based optimization, and multi-video synopsis, showcasing the algorithm's flexibility ...
doi:10.5281/zenodo.11032718
fatcat:cfsu6nlqgbca5cm3nk2vuuxj44
Collective Motion and Self-Organization of a Swarm of UAVs: A Cluster-Based Architecture
2021
Sensors
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Lastly, this article compares the designed algorithm with the NSGA-II model to show that the proposed model has better convergence and durability, both in the individual clusters and inside the greater ...
To address the aforesaid issues, this paper designs a hybrid meta-heuristic algorithm by merging the particle swarm optimization (PSO) with the multi-agent system (MAS). ...
Comparison with NSGA-II To test the efficiency of the designed strategy, this paper first compares it with the genetic algorithm NSGA-II. ...
doi:10.3390/s21113820
pmid:34073061
fatcat:3nl3zsbxyrbuzjw3qwtipwiwui
Research Progress on Synergistic Technologies of Agricultural Multi-Robots
2021
Applied Sciences
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multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics ...
Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of ...
We also thank the critical comments and suggestions from the anonymous reviewers for improving the manuscript.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app11041448
fatcat:sk5eu5j62vg6rkys62qhxzhphq
A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems
2017
IEEE Communications Surveys and Tutorials
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2016 pre-print arXiv:1609.04069v1 fatcat:f7f3ddlmrrgndkui7seh4wojsm
Then, we elaborate on various prevalent approaches conceived for MOO, such as the family of mathematical programming based scalarization methods, the family of heuristics/metaheuristics based optimization ...
Wireless sensor networks (WSNs) have attracted substantial research interest, especially in the context of performing monitoring and surveillance tasks. ...
In [101] , Jia et al. proposed a new coverage control scheme based on an improved NSGA-II using an adjustable sensing radius. ...
doi:10.1109/comst.2016.2610578
fatcat:muagmfeguzbshb5w7ceaxddapm
Fleets of robots for environmentally-safe pest control in agriculture
2016
Precision Agriculture
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Feeding the growing global population requires an annual increase in food production. ...
To reduce pesticide input and preserve the environment while maintaining the necessary level of food production, the efficiency of relevant processes must be drastically improved. ...
The authors appreciate the contributions of Airrobot Gmbh & Co Kg, Bluebotics SA and the CM S.r.l members of the RHEA consortium not participating in this article. ...
doi:10.1007/s11119-016-9476-3
fatcat:kuqplcc6o5hvneoevvksbj5era
A Mission Planning Approach for Precision Farming Systems Based on Multi-Objective Optimization
2018
Sensors
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In order to solve MOP, an improved algorithm, MP-PSOGA, is proposed, taking advantages of the Genetic Algorithms and Particle Swarm Optimization. ...
Their research is done in correlation with the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) project and focuses on the underwater mission planning for different robots, like Unmanned ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s18061795
pmid:29865251
pmcid:PMC6021986
fatcat:r7rbuo7pibaxpgs7dx6fm2y7pq
A survey on multi-robot coverage path planning for model reconstruction and mapping
2019
SN Applied Sciences
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Coverage path planning (CPP) is one of the active research topics that could benefit greatly from multi-robot systems. ...
In this paper, we surveyed the research topics related to multi-robot CPP for the purpose of mapping and model reconstructions. ...
Based on the surveyed papers, the main future application domains of multi-robot CPP include search and rescue, inspection, and agriculture. ...
doi:10.1007/s42452-019-0872-y
fatcat:y6hkwvnapnfpnax3k7xnqkj2gi
Heuristics for Multi-Vehicle Routing Problem Considering Human-Robot Interactions
[article]
2022
arXiv
pre-print
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For larger instances, a variable neighborhood search algorithm is offered to compute near optimal solutions and address the challenges that arise when solving the combinatorial multi-objective routing ...
We consider a multi-objective, multiple-vehicle routing problem in which teams of manned ground vehicles (MGVs) and UGVs are deployed respectively in a leader-follower framework to execute missions with ...
They apply VNS to eight different realistic scenarios and conclude that the multi objective VNS approach is superior in comparison to the NSGA. ...
arXiv:2208.09607v1
fatcat:ze5ixnaucjfjtoi2gwqtzmdoey
Real-Time Task Allocation of Heterogeneous Unmanned Aerial Vehicles for Search and Prosecute Mission
2021
Wireless Communications and Mobile Computing
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Finally, we design some simulation experiments and compare with the task allocation algorithm based on resource welfare. ...
In this paper, we study the real-time task allocation problem of heterogeneous UAVs searching and delivering goods in the city. ...
Acknowledgments This work was supported in part by the National Natural Sci- ...
doi:10.1155/2021/5516086
fatcat:xfz4pm4x6vgr7omxit24orjbnu
Robust Trajectory-Tracking for a Bi-Copter Drone Using Indi: A Gain Tuning Multi-Objective Approach
2022
Robotics
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The linear control providing inputs to the NDI and INDI controllers is tuned via a novel multi-objective optimization auto-tuning method using the non-dominated sorting genetic algorithm II (NSGA-II). ...
This paper presents an optimized robust trajectory control system for an autonomous tiltrotor bi-copter based on an incremental nonlinear dynamic inversion (INDI) strategy combined with a set of PID/PD ...
process based on the NSGA-II algorithm is used to minimize the two error functions. ...
doi:10.3390/robotics11050086
fatcat:mvkja2bcjzc43gqbouh6l6tcme
A comprehensive survey: Applications of multi-objective particle swarm optimization (MOPSO) algorithm
2013
Transactions on Combinatorics
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This paper reviews all the applications of MOPSO in miscellaneous areas followed by the study on MOPSO variants in our next publication. ...
Numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of Multi-Objective Optimization (MOO) had arisen several years ago. ...
Acknowledgments The authors wish to thank the Executive Director, Birla Institute of Scientific Research for the support given during this work. We are thankful to Dr. ...
doaj:d067a695f2874248a87829b843ff1df7
fatcat:l2vav6okc5bcdaci3h2hwoktyy
[ICNSC 2020 Front Matter]
2020
2020 IEEE International Conference on Networking, Sensing and Control (ICNSC)
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We explain such research directions Finally we will report recent resulted of deep learning understanding of video pictures based on Masking Vision Based Autonomous Navigation. Speaker Biography Dr. ...
The two kinds of ANN collaborate to solve the quadratic mean-variance problems in the way that the upper level ANN selects optimal neurons and the lower level ANN decided each optimal weights. ...
sorting genetic algorithm-II (NSGA-II), multi-objective particle swarm optimization (MOPSO), and game-theoretic based greedy algorithms (GTBGA), in terms of optimality of scheduling plans yielded. single ...
doi:10.1109/icnsc48988.2020.9311391
fatcat:e7vdat475ncofjhzmdwwpuy23y
Drone-Aided Delivery Methods, Challenge, and the Future: A Methodological Review
2023
Drones
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We then categorize the literature according to the characteristics and objectives of the problems and thoroughly analyze them based on mathematical formulations and solution techniques. ...
With the increasing interest in this technology, it is crucial for researchers and practitioners to understand the current state of the art in drone delivery. ...
The research applied a modified Non-dominated Sorting Genetic Algorithm II (NSGA-II) to solve the model, which includes double-layer coding. Khoufi et al. ...
doi:10.3390/drones7030191
fatcat:inuqdjb5m5e6dk2qvxtdlioepe
Path Planning for UAV Communication Networks: Related Technologies, Solutions, and Opportunities
2022
ACM Computing Surveys
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In this paper, the advantages and disadvantages of each path planning algorithm and the functional problems. ...
We first introduce the network structure and performance evaluation of UAVCN. We then investigate the generic UAV path planning algorithms and the path planning algorithms in UAVCN. ...
NSGA-II is improved by using the ranking-based wheel selection and local search method in [56] to avoid unnecessary saw tooth movement. ...
doi:10.1145/3560261
fatcat:pcqxrenolrdezkz2bx6cmb7zvu
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