Search Results - (( model evaluation genetic algorithm ) OR ( based formulation based algorithm ))

Genetic algorithm based signal optimizer for oversaturated urban signalized intersection by Tan, Min Keng, Chuo, Helen Sin Ee, Chin, Renee Ka Yin, Kiam, Beng Yeo, Teo, Kenneth Tze Kin

“…Therefore, this work proposes genetic algorithm (GA) to optimize the traffic signals for reducing the average delay at the at-grade crossed intersection under oversaturated condition. …”
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Multiaxial Fatigue Life Modelling using Hybrid Approach of Critical Plane and Genetic Algorithm by M., Kamal, M. M., Rahman

“…This paper presents a new hybrid approach for multiaxial fatigue life estimation, based on continuum damage mechanics theory and a genetic algorithm with critical plane model formulation. …”
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Enhanced genetic algorithm optimization model for a single reservoir operation based on hydropower generation: case study of Mosul reservoir, northern Iraq by Al‑Aqeeli, Yousif H., Lee, Teang Shui, Abd Aziz, Samsuzana

“…The purpose of this study was to formulate and improve an approach of a genetic algorithm optimization model (GAOM) in order to increase the maximization of annual hydropower generation for a single reservoir. …”
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Modeling and prediction of the specific heat capacity of Al₂O₃/water nanofluids using hybrid genetic algorithm/support vector regression model by Alade, Ibrahim Olanrewaju, Abd Rahman, Mohd Amiruddin, Saleh, Tawfik A.

“…The proposed (genetic algorithm/support vector regression) GA/SVR model was formulated using volume fractions and specific heat capacities of the alumina nanoparticles. …”
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Multi-objective genetic algorithm driven formulation of a plant-based probiotic premix powder: Nutrient-cost modeling, microstructural characterization and sensory validation by Tang, Ping, Cui, Ming Yang, Mohsin, Aliah Zannierah, Meor Hussin, Anis Shobirin, Juhari, Nurul Hanisah

“…This study presents a multi-objective genetic algorithm (NSGA-II) driven framework for the rational formulation of a plant-based probiotic premix powder under simultaneous nutritional and economic constraints. …”
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Application of an evolutionary algorithm-based ensemble model to job-shop scheduling by Tan, Choo Jun, Neoh, Siew Chin, Lim, Chee Peng, Hanoun, Samer, Wong, Wai Peng, Loo, Chu Kiong, Zhang, Li, Nahavandi, Saeid

“…Specifically, a modified micro genetic algorithm (MmGA) is used as the building block to formulate an ensemble model to undertake multi-objective optimisation problems in job-shop scheduling. …”
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An immune-genetic algorithm with tabu local search for network intrusion detection system / Hamizan Suhaimi by Suhaimi, Hamizan

“…This research aim is to study the performance of an improvised Genetic Algorithm (GA) by formulating its problem-specific algorithm for network intrusion problem. …”
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Dual-Criteria Method For Determining Critical Plane Orientation For Multiaxial Fatigue Prediction Using A Genetic Algorithm by M., Kaamal, M. M., Rahman

“…It is required to maintain greater accuracy than the incremental angle methods used conventionally in critical plane searching algorithms. The multi-criteria-based critical plane selection method is evaluated; the considered criteria include a fatigue parameter and variance of shear stress, both maximized to find the most damaging plane. …”
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Multi-state PSO GSA for solving discrete combinatorial optimization problems by Ismail, Ibrahim

“…The multistate model is then implemented in PSO and GSA. As a consequence, multi-state particle swarm optimization (MSPSO) and multi-state gravitational search algorithm (MSGSA) are developed. …”
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Optimization of operations of reservoir systems for hydropower generation in Tigris River Basin, Iraq by Al-Aqeel, Yousif Hashim Abdullah

“…The performances of these two algorithms were evaluated through comparing their optimal values. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…This study is primarily aimed at investigating two issues in genetic algorithm (GA) and one issue in conformational search (CS) problems. …”
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Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam by Toghroli, Ali, Suhatril, Meldi, Ibrahim, Zainah, Safa, Maryam, Shariati, Mahdi, Shamshirband, Shahaboddin

“…Estimation and prediction results of the ELM models were compared with genetic programming (GP) and artificial neural networks (ANNs) models. …”
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Evaluation method of rationality of urban landscape facility design based on neural network by Wang, Fanglong, Zhuang, Qianda, Sun, Xiaoni, Lin, Dengfeng

“…Therefore, this study formulates a scientific and reasonable evaluation index system for the rationality of urban landscape facility design and uses a neural network to carry out intelligent evaluation, in order to obtain optimal evaluation outcomes. …”
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Capacity planning for mixed-load tester under demand and testing time uncertainty by Asih, Hayati Mukti

“…Currently,the company’s issue is low tester utilization of about 71%,well below the target of 96%.The objective of this research is to improve tester utilization while achieving the production target under uncertain demand and testing time and also to determine the break-even point on the testers required.A novel approach of integrating a mathematical model,robust optimization model,genetic algorithm,simulation model and cost–volume –profit analysis was developed.Firstly,a mathematical model of mixed-load tester was formulated.Next,a set of discrete scenarios was proposed to address uncertain demand and testing time.A robust optimization and genetic algorithm model was developed to optimize the number of testers under the described uncertainties.Next,these scenarios were simulated using the Pro Model simulation software to validate the proposed models and to evaluate throughput and tester utilization.Finally,the cost–volume–profit analysis was performed for scenarios that require additional testers at various levels of uncertainties.The results showed that the proposed solution improved tester utilization by 25% compared to the current system.This research has contribution by developing novel hybrid methodology and able to provide useful insights to assist company’s managers to plan and allocate resources according to variations in customers’ demands and testing time.…”
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Similarity reasoning-driven evolutionary fuzzy system for monotonic-preserving models by Jee, Tze Ling

“…An optimization tool, i.e., genetic algorithm (GA), is further implemented. The applicability of the proposed framework is demonstrated and evaluated wi,th two real problems, i.e., education assessment problem and failure analysis problem. …”
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Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function by Tan, Min Keng

“…This study aims to explore the potential of implementing multi-agent-based Genetic Algorithm (GA) with interactive metamodel to acquire regular optimisation on dynamic characteristic of traffic flow. …”
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

“…In order to increase the system efficiency and maximize the power generation, constructed operation models were optimized. To determine the optimum solution in each policy, real coded genetic algorithm is used as an optimization technique. …”
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Optimization ofhybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization by Siti Nurhazwani Husna, Mohd Hata, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…The EE-HFS was optimized using Multi-Objective Tiki Taka Optimization (MOTTA).The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation.The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi-ObjectiveEvolutionary Algorithm Based on Decomposition, the Multi-ObjectiveParticle Swarm Optimization,and the recent algorithm,the Multi-ObjectiveGrey Wolf Optimizer. …”
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Optimization of hybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization by Siti Nurhazwani Husna, Mohd Hata, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation. The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi Objectives Evolutionary Algorithm Based on Decomposition, the Multi Objectives Particle Swarm Optimization, and the recent algorithm Multi Objectives Grey Wolf Optimizer. …”
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A new fuzzy criterion-referenced assessment with a fuzzy rule selection technique and a monotonicity-preserving similarity reasoning scheme by Jee, T.L, Tay, K.M, Ng, CK

“…Selected rules are identified in such that the unselected rules can be deduced via a monotonicity-preserving SR technique. We formulate the process of minimizing the number of selected rules as a constrained optimization problem and a genetic algorithm (GA) technique is implemented. …”
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