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Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm by ,, Dwi Pebrianti, Ann Ayop azmi, Nurnajmi Qasrina, Bayuaji, Luhur, Suarin, Nur Aisyah Syafinaz, ,, Muhammad Syafrullah

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Performance evaluation of PID controller parameters gain optimization for wheel mobile robot based on bat algorithm and particle swarm optimization by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Nurnajmin Qasrina, Ann, Bayuaji, Luhur, Syafrullah, Muhammad, Riyanto, Indra

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Performance evaluation of PID controller parameters gain optimization for wheel mobile robot based on bat algorithm and particle swarm optimization by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Nurnajmin Qasrina, Ann, Luhur, Bayuaji, Muhammad, Syafrullah, Indra, Riyanto

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Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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A comprehensive overview of classical and modern route planning algorithms for self-driving mobile robots by Wan Daud, Wan Mohd Bukhari, Abu, Nur Syuhadah, Omar, Siti Nashayu, Sohaimeh, Shahirul Ashraf, Adli,, M. H.

“…Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. …”
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Bat optimized link state routing protocol for energy-aware mobile ad-hoc networks by Jubair M.A., Mostafa S.A., Muniyandi R.C., Mahdin H., Mustapha A., Hassan M.H., Mahmoud M.A., Al-Jawhar Y.A., Al-Khaleefa A.S., Mahmood A.J.

“…The symmetry between OLSR of MANET and Bat Algorithm (BA) is that both of them use the same mechanism for finding the path via sending and receiving specific signals. …”

Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

“…Both Bat Algorithm parameters and AFW parameters are adaptively tuned to balance exploration and exploitation throughout the optimization process. …”
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Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

“…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling by Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

“…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
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Harris Hawk Optimization-Based Deep Neural Networks Architecture for Optimal Bidding in the Electricity Market by Kavita Jain, Muhammed Basheer Jasser, Muzaffar Hamzah, Akash Saxena, Ali Wagdy Mohamed

“…In this research, we provide HHO-NN (Harris Hawk Optimization-Neural network), a novel algorithm based on Harris Hawk Optimization (HHO) that is capable of fast convergence when compared to previous evolutionary algorithms for automatically searching for meaningful multilayered perceptron neural networks (MPNNs) topologies for optimal bidding. …”
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Towards Wind Energy-based Charging Stations: A Review of Optimization Methods by Alhasan A.M.W., Umar D.A., Alkawsi G., Alkahtani A.A., Alomari M.A., Aris H.

“…Singular reliance on a solitary algorithm or software for charging utility optimization is discerned to be potentially limiting. …”

Maximizing DRL-based energy efficiency in IRS-NOMA using a DDPG algorithm for the next generation of wireless communications by Audah, Kamil, Noordin, Nor K., Hussein, Wala'a, Rasid, Mod Fadlee B. A., Sali, Aduwati, Flah, Aymen

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Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks by Iranpanah, Havzhin

“…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
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Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach by Premkumar M., Hashim T.J.T., Ravichandran S., Sin T.C., Chandran R., Alsoud A.R., Jangir P.

“…Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. …”

Energy-efficient power allocation for downlink non orthogonal multiple access networks based on game theory and genetic algorithm / Reem Mustafa Mah’d Al Debes by Reem Mustafa , Mah’d Al Debes

“…The research leverages Artificial Intelligence (AI)-based Genetic Algorithms (GA) and game theory to address critical challenges in resource allocation. …”
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Optimizing Cloud Storage Costs: Introducing the Pre-Evaluation-Based Cost Optimization (PECSCO) Mechanism by Alomari M.F., Mahmoud M.A., Gharaei N., Rasool S.M., Hasan R.A.

“…The core of the algorithm utilizes a Genetic Algorithm (GA) to find the optimal position for the first evaluator by minimizing the total distance between this evaluator and all CCTV nodes, aiming for surveillance efficiency. …”

Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid by Ariya Sinhalage Buddhika Eshan Karunarathne

“…In addition, the solutions have been evaluated based on pre-defined performance metrics and the outcomes of the optimization framework were compared with the other existing optimization techniques to evaluate the potency and the productivity of the developed MLPSO algorithm. …”

Dam haji game using A* search algorithm / Siti Farah Najwa Mukhlis by Mukhlis, Siti Farah Najwa

“…In Dam Haji game, the goal is to find the optimal movement to make, so A* algorithm, which is a pathfinding algorithm is used. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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An exponential based simulated kalman filter algorithm for data-driven PID tuning in liquid slosh controller by Mohd Falfazli, Mat Jusof, Ahmad Nor Kasruddin, Nasir, Mohd Ashraf, Ahmad, Zuwairie, Ibrahim

“…SKF is a random based optimization algorithm inspired from a Kalman Filter theory. …”
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