Search Results - pareto optimization ((method algorithm) OR (means algorithm))

Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering by Rashed, Alwatben Batoul

“…It was superior to the clustering algorithm methods in most real-world datasets with means ARI of over 0.35. …”
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Evaluating the effectiveness of integrated benders decomposition algorithm and epsilon constraint method for multi-objective facility location problem under demand uncertainty by Rahimi, Iman, Tang, Sai Hong, Ahmadi, Abdollah, Ahmad, Siti Azfanizam, Lee, Lai Soon, Sharaf, Adel M.

“…One of the most challenging issues in multi-objective problems is finding Pareto optimal points. This paper describes an algorithm based on Benders Decomposition Algorithm (BDA) which tries to find Pareto solutions. …”
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Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD) by Rashed, Alwatben Batoul, Hamdan, Hazlina, Mohd Sharef, Nurfadhlina, Sulaiman, Md Nasir, Yaakob, Razali, Abubakar, Mansir

“…The proposed method was evaluated against five clustering approaches that have succeeded in optimization that comprises of K-means Clustering, MCPSO, IMCPSO, Spectral clustering, Birch, and average-link algorithms. …”
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A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN by BISWAS, KALLOL

“…Better performances were observed in cases of Pareto optimal front, search capabilities, and diversity of solutions by comparing the proposed method with other standard methods like MOCPSO, MOGWO, and MOPSO. …”
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Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

Petroleum Refinery Planning Under Uncertainty: A Multiobjective Optimization Approach with Economic and Operational Risk Management by Van Fu Shen, Fu Shen

“…The two stage stochastic risk model is then reformulated using Mean Absolute Deviation as the risk measure. After formulating the stochastic model using Mean Absolute Deviation, the problem is then investigated using the Pareto front solution of efficient frontier of the resulting multiobjective optimization problem by using the Weighted Sum Method as well as the ε-constraint method in order to obtain the Pareto Optimal Curve which generates a wide selection of optimization solutions for our problem. …”
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Petroleum Refinery Planning Under Uncertainty: A Multiobjective Optimization Approach with Economic and Operational Risk Management by Van, Fu Shen

“…The two stage stochastic risk model is then reformulated using MeanAbsolute Deviation as the risk measure. After formulating the stochastic model using Mean Absolute Deviation, the problem is then investigated using the Pareto front solution of efficient frontier of the resulting multiobjective optimization problem by using the Weighted SumMethod as well as the e-constraint method in order to obtain the Pareto Optimal Curve which generates a wide selection of optimization solutions for our problem. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour M., Ali Z., Othman M.M., Bo R., Javadi M.S., Ridha H.M., Alrifaey M.

“…The proposed method is a version of the democratic political optimization algorithm in which the search capability of this method to cover the borders of the Pareto frontier is enhanced. …”

Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes by Nor Atiqah, Zolpakar, Lodhi, Swati Singh, Pathak, Sunil, Sharma, Mohita Anand

“…Multi-objectives Genetic Algorithm (MOGA) is one of many engineering optimization techniques, a guided random search method. …”
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Scheduling scientific workflow in multi-cloud: a multi-objective minimum weight optimization decision-making approach by Farid, Mazen, Heng, Siong Lim, Chin, Poo Lee, Latip, Rohaya

“…A significant number of NP-hard problem optimization methods employ multi-objective algorithms. …”
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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

“…The IEEE RTS 26, 32 and 36-unit dataset systems were used in the performance evaluation of the PACS algorithm. The performance of PACS algorithm was compared against four benchmark multi-objective algorithms including the Nondominated Sorting Genetic, Strength Pareto Evolutionary, Simulated Annealing, and Particle Swarm Optimization using the metrics grey relational grade (GRG), coverage, distance to Pareto front, Pareto spread, and number of non-dominated solutions. …”
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Reservoir system modelling using nondominated sorting genetic algorithm in the framework of climate change by Nurul Nadrah Aqilah, Tukimat

“…In conclusion, this finding contributes toward the development of models using evolution algorithm and statistical methods for sustainable water resources planning and management in the context of future climate change…”
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Hybrid multi-objective optimization methods for in silico biochemical system production by Mohd Arfian, Ismail

“…The proposed method combined Newton method, Strength Pareto approach, Cooperative Coevolutionary Algorithm (CooCA) and Genetic Algorithm (GA). …”
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Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm by Muthana, Shatha Abdulhadi, Ku Mahamud, Ku Ruhana

“…In any metaheuristic, the parameter values strongly affect the efficiency of an algorithm’s search. This research aims to find the optimal parameter values for the Pareto Ant Colony System (PACS) algorithm, which is used to obtain solutions for the generator maintenance scheduling problem. …”
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Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system by Ridha, Hussein Mohammed, Gomes, Chandima, Hizam, Hashim, Mirjalili, Seyedali

“…The paper presents a new multiple scenario multi-objective salp swarm optimization (MS-MOSS) algorithm to optimally size a standalone PV system. …”
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Solution of optimal power flow using non-dominated sorting multi-objective based hybrid firefly and particle swarm optimization algorithm by Abdullah Khan, Hizam, Hashim, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi

“…Pareto optimal front was obtained by using non-dominated sorting and crowding distance methods. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…Second of all, this study operates within experimental design with Taguchi method to discover the optimal design factors for the two proposed genetic operators. …”
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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

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Multi-objective selection and structural optimization of the gantry in a gantry machine tool for improving static, dynamic, and weight and cost performance by Besharati, S.R., Dabbagh, V., Amini, H., Sarhan, Ahmed Aly Diaa Mohammed, Akbari, J., Abd Shukor, Mohd Hamdi, Ong, Zhi Chao

“…In this investigation, the multi-objective selection and optimization of a gantry machine tool is achieved by analytic hierarchy process, multi-objective genetic algorithm, and Pareto-Edgeworth-Grierson-multi-criteria decision-making method. …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

“…The results obtained are then analysed to assess the proposed solution’s performance in obtaining each deployment objective’s optimal value. Finally, the proposed algorithm’s effectiveness regarding node coverage, energy consumption, Pareto-optimal value, and algorithm execution time is validated using three Pareto-optimal metrics: including inverted generation distance (IGD), hypervolume, and diversity. …”
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