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A hybrid particle swarm optimization approach and its application to solving portfolio selection problems by Shamshul Bahar, Yaakob, Prof. Madya, Watada, Junzo

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Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

“…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

“…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

“…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

“…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

“…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

“…This algorithm synergizes the ABC algorithm and Artificial Rabbits Optimization (ARO) algorithm. …”
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Migrating Birds Optimization based Strategies for Pairwise Testing by Hasneeza, L. Zakaria, Kamal Z., Zamli

“…Two strategies have been proposed; the first strategy implements the basic MBO algorithm, called Pairwise MBO Strategy (PMBOS) and the second strategy implements an improved Pairwise MBO strategy, called iPMBOS. …”
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Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir

“…Gradient-based Mutation MRFO (GbM-MRFO) is derived from basic strategy of MRFO and synergized with the Gradient-based Mutation strategy. …”
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The design and applications of the african buffalo algorithm for general optimization problems by Odili, Julius Beneoluchi

“…Optimization, basically, is the economics of science. …”
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Inverse kinematics of six degrees of freedom robot manipulator based on improved dung beetle optimizer algorithm by Haohao, Ma, As’arry, Azizan, Haoyang, Zhang, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi, Zuhri, Mohd Yusoff Moh, Delgoshaei, Aidin

“…This paper proposed an improved spiral search multi-strategy dung beetle optimizer (DBO) algorithm for solving the inverse kinematics problem. …”
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

“…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…There are two basic strategies in using hybrid GAs, Lamarckian and Baldwinian evolution. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

“…In future, this work could be enhanced for better performances in both aspects using another variant of the PSO or other potential metaheuristic searching techniques such as Firefly Optimization, Bat Algorithm and etc.…”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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Ant system with heuristics for capacitated vehicle routing problem by Tan, Wen Fang

“…As a route improvement strategy, two heuristics which are the swap among routes procedure and 3-opt algorithm are also employed within the ASH algorithm. …”
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