From Integer Programming to Machine Learning: A Technical Review on Solving University Timetabling Problems by Xin Gu, Muralee Krish, Shaleeza Sohail, Sweta Thakur, Fariza Sabrina, Zongwen Fan

“…We identify that the implementation rate of models using integer programming is 98%, which is much higher than 34% implementation rates using meta-heuristics algorithms from the existing review. The integer programming models are analysed by the problem types, solutions, tools, and datasets. …”
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A New Mathematical Model for Cell Layout Problem considering Rotation of Unequal Dimensions of Cells and Machines by Raheleh Alamiparvin, Esmaeil Mehdizadeh, Hamed Soleimani

“…Finally, the parameters of the three meta-heuristic algorithms were set by the Taguchi method. Numerical results indicated that ICA was superior to both the PSO algorithm and GA. …”
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Static and Dynamic Routing, Fiber, Modulation Format, and Spectrum Allocation in Hybrid ULL Fiber-SSMF Elastic Optical Networks by Kangao Ouyang, Fengxian Tang, Zhilin Yuan, Jun Li, Yongcheng Li

“…We formulated this RFMSA problem as a node-arc based Mixed Integer Linear Programming (MILP) model and developed Spectrum Window Plane (SWP)-based heuristic algorithms based on different fiber selection strategies, including spectrum usage based (SU), optical signal-to-noise ratio (OSNR) aware, ULL fiber first (UFF), and random strategies. …”
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Multijunction solar cell parameter estimation based on metaheuristic algorithms by Marwa M. Elzalabani, Doaa M. Atia, Aref Y. Eliwa, Belal A. Abou Zalam, Mahmoud S. AbouOmar

“…In addition, The Newton-Raphson Method (NRM) hybrid with meta-heuristic algorithms, or MOAs, is used to improve solution estimates, accelerate convergence rates, reduce computational costs, and enhance robustness. …”
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IHSCR: Energy-efficient clustering and routing for wireless sensor networks based on harmony search algorithm by Bing Zeng, Yan Dong, Xinyu Li, Liang Gao

“…As clustering and routing for improving the energy efficiency of wireless sensor networks are NP-hard problems, increasing meta-heuristic algorithms are introduced for solving them. However, due to their discreteness and strong constraints, most meta-heuristics are unsuitable or inefficient to optimize them. …”
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Comprehensive Fault Location on Transmission Lines Considering Variation in Line Parameters and Saturation in Current Transformers by Duy C. Huynh, Loc D. Ho

“…Numerical results and comparisons confirm the proposal’s effectiveness, being better than the previous traditional fault location technique such as the impedance-based (IB) technique, as well as other meta-heuristic algorithms such as a grey wolf optimization (GWO) algorithm, a gravitational search (GS) algorithm, and an inclined planes optimization (IPO) algorithm. …”
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