A Pareto-based Optimizer for Workflow Scheduling in Cloud Computing Environment by Azade Khalili, Seyed Morteza Babamir

“…Due to the heterogeneity and dynamicity of VMs and diversity of tasks size, workflow scheduling is confronted with a huge permutation space and is known as an NP-complete problem; therefore, heuristic algorithms are used to reach an optimal scheduling. …”
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Contribution of parallel NSGA-II in optimal design of water distribution networks by Artina, S, Bragalli, C, Marchi, A, Erbacci, G, Rivi, M

“…Among these, multi-objective heuristic algorithms are interesting because of their capacity for dealing with separate objectives that allow us to choose a posteriori the best compromise, but one of their main drawbacks is the long time required to obtain good solutions. …”

CAPSO: centripetal accelerated particle swarm optimization by Beheshti, Zahra, Shamsuddin, Siti Mariyam

“…Swarm intelligence (SI) algorithms comprise a branch of meta-heuristic algorithms that imitate the behavior of insects, birds, fishes, and other natural phenomena to find solutions for complex optimization problems. …”

Towards machine learning for error compensation in additive manufacturing by Omairi, Amzar, Ismail, Zool Hilmi

“…This paper presents a comprehensive survey on commonly used predictive models based on heuristic algorithms and discusses their applications toward making AM “smart”. …”

Mathematical formulation of tabu search in combinatorial optimization by Ismail, Zuhaimy

“…Tabu Search (TS) is a heuristic method based on the use of prohibition-based techniques and basic heuristics algorithms like local search. The main advantage of TS with respect to other conventional search is in the intelligent use of past history of the search to influence its future search procedures. …”
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Comparative Study of Adaptive Elitism and Mutation Operators in Flower Pollination Algorithm for Combinatorial Testing Problem by Abdullah, Nasser, Kamal Z., Zamli

“…Flower Pollination Algorithm (FPA) is one of the recent meta-heuristic algorithms for global optimization. Although proven to be efficient, FPA is prone to get stuck into a local optimum due to the weakness of its population’s diversity especially for multimodal optimization problem. …”
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A Hybrid Moth Flame Optimization and Golden Jackal Optimization Algorithm Based Opposition for Global Optimization Problems by Zhaobin Qiu, Ying Qiao

“…To evaluate the effectiveness of the proposed algorithm, we compare it with 10 other meta-heuristic algorithms using 30 benchmark functions, and perform statistical tests on the results. …”
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A Robust Single-Machine Scheduling Problem with Two Job Parameter Scenarios by Gang Xuan, Win-Chin Lin, Shuenn-Ren Cheng, Wei-Lun Shen, Po-An Pan, Chih-Ling Kuo, Chin-Chia Wu

“…Next, three scenario-dependent heuristic algorithms are proposed. Additionally, a population-based iterated greedy algorithm is proposed in the hope of increasing the diversity of the solutions. …”
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A Minimum Cost Design Approach for Steel Frames Based on a Parallelized Firefly Algorithm and Parameter Control by Gregorio Sánchez-Olivares, Antonio Tomás, Salvador García-Ayllón

“…To reduce the calculation time, which is a common problem of meta-heuristic algorithms when they are used to solve real design cases, and to better suit the characteristics of the algorithm, a parallel migration strategy has been implemented and tested. …”
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Heuristic initialization of PSO task scheduling algorithm in cloud computing by Seema A. Alsaidy, Amenah D. Abbood, Mouayad A. Sahib

“…In this paper, an improved initialization of particle swarm optimization (PSO) using heuristic algorithms is proposed. Longest job to fastest processor (LJFP) and minimum completion time (MCT) algorithms are used to initialize the PSO. …”
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An Investigation of Particle Swarm Optimization Topologies in Structural Damage Detection by Xiao-Lin Li, Roger Serra, Julien Olivier

“…Adopting meta-heuristic algorithms, in which particle swarm optimization (PSO) is the most widely used, is a popular approach. …”
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K-Means Clustering Algorithm Based on Chaotic Adaptive Artificial Bee Colony by Qibing Jin, Nan Lin, Yuming Zhang

“…Finally, the confluent algorithm is compared with other stochastic heuristic algorithms on the 20 standard test functions and 11 datasets. …”
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Novel Supervisory Management Scheme of Hybrid Sun Empowered Grid-Assisted Microgrid for Rapid Electric Vehicles Charging Area by Zeeshan Ahmad Arfeen, Md Pauzi Abdullah, Usman Ullah Sheikh, Mehreen Kausar Azam, Aliyu Hamza Sule, Ghulam Fizza, Hameedah Sahib Hasan, Muhammad Ashfaq Khan

“…The optimum cost is calculated using heuristic algorithms in compliance with the meta-heuristic barebones Harris hawk algorithm. …”
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A Hybrid Multitask Learning Framework with a Fire Hawk Optimizer for Arabic Fake News Detection by Mohamed Abd Elaziz, Abdelghani Dahou, Dina Ahmed Orabi, Samah Alshathri, Eman M. Soliman, Ahmed A. Ewees

“…In this paper, we propose a disinformation detection framework based on multi-task learning (MTL) and meta-heuristic algorithms in the context of the COVID-19 pandemic. …”
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Simplified Deep Reinforcement Learning Based Volt-var Control of Topologically Variable Power System by Qing Ma, Changhong Deng

“…Traditional mathematical or heuristic algorithms are increasingly incompetent for this task because of the slow online calculation speed. …”
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CLTSA: A Novel Tunicate Swarm Algorithm Based on Chaotic-Lévy Flight Strategy for Solving Optimization Problems by Yi Cui, Ronghua Shi, Jian Dong

“…Afterwards, the TLTSA was selected for comparative research with other well-known meta-heuristic algorithms. The 16 unimodal benchmark functions, 14 multimodal benchmark functions, 6 fixed-dimension functions, and 3 constrained practical problems in engineering were selected to verify the performance of TLTSA. …”
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A Quantum Annealing Bat Algorithm for Node Localization in Wireless Sensor Networks by Shujie Yu, Jianping Zhu, Chunfeng Lv

“…Simulation results show that, compared with other heuristic algorithms, the convergence speed and solution accuracy of QABA are greatly improved, with the highest average error of QABA-2D reduced by 90.35% and the lowest by 17.22%, and the highest average error of QABA-3D reduced by 75.26% and the lowest by 7.79%.…”
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SLA-DQTS: SLA Constrained Adaptive Online Task Scheduling Based on DDQN in Cloud Computing by Kaibin Li, Zhiping Peng, Delong Cui, Qirui Li

“…We evaluate the performance of the algorithm by comparing it with three heuristic algorithms (Min-Min, random, and round robin) under different loads. …”
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Domain Knowledge-Based Evolutionary Reinforcement Learning for Sensor Placement by Mingxuan Song, Chengyu Hu, Wenyin Gong, Xuesong Yan

“…Extensive experiments have been conducted and the results show that our proposed algorithm outperforms meta-heuristic algorithms and deep reinforcement learning (DRL).…”
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An Exact Algorithm for Task Allocation of Multiple Unmanned Surface Vehicles with Minimum Task Time by Kai Xue, Zhiqin Huang, Ping Wang, Zeyu Xu

“…Most of the research lines of task allocation are using heuristic algorithms to obtain suboptimal solutions to reduce both the max task cost and total task cost. …”
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