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

Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system by Ridha, Hussein Mohammed, Gomes, Chandima, Hizam, Hashim, Mirjalili, Seyedali

“…Loss of load probability (LLP) and life-cycle cost (LLC) are considered to obtain the Pareto front. The iterative method is employed for validation of the superiority results of the proposed MS-MOSS algorithm. …”
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Multi-objective PMU placement optimization considering the placement cost including the current channel allocation and state estimation accuracy by Matsukawa, Yoshiaki, Watanabe, Masayuki, Mitani, Yasunori, Othman, Mohammad Lutfi

“…The current channel selection is represented as a decision variable in the optimization. For those trade-off objective functions, the Pareto approach by Non-dominated Sorting Genetic Algorithm II (NSGA-II) is applied in the optimization. …”
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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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Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering by Rashed, Alwatben Batoul

“…However, the PSO algorithm produces a group of non-dominated solutions which makes the choice of a “suitable” Pareto optimal or non-dominated solution more difficult. …”
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Optimum design of a standalone solar photovoltaic system based on novel integration of iterative-PESA-II and AHP-VIKOR methods by Ridha, Hussein Mohammed, Gomes, Chandima, Hizam, Hashim, Ahmadipour, Masoud, Muhsen, Dhiaa Halboot, Ethaib, Saleem

“…In this study, a novel hybrid sizing approach was developed on the basis of techno-economic objectives to optimally size the SAPV system. The proposed hybrid method consisted of an intuitive method to estimate initial numbers of PV modules and storage battery, an iterative approach to accurately generate a set of wide ranges of optimal configurations, and a Pareto envelope-based selection algorithm (PESA-II) to reduce large configuration by efficacy obtaining a set of Pareto front (PF) solutions. …”
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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.

Optimum design of a standalone photovoltaic system based on integration of iterative-PESA-II and AHP-VICKOR methods by Ridha, Hussein Mohammed, Gomes, Chandima, Hizam, Hashim, Ahmadipour, Masoud, Muhsen, Dhiaa Halboot, Ethaib, Saleem

“…In this study, a novel hybrid sizing approach was developed on the basis of techno-economic objectives to optimally size the SAPV system. The proposed hybrid method consisted of an intuitive method to estimate initial numbers of PV modules and storage battery, an iterative approach to accurately generate a set of wide ranges of optimal configurations, and a Pareto envelope-based selection algorithm (PESA-II) to reduce large configuration by efficacy obtaining a set of Pareto front (PF) solutions. …”
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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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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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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

“…In an attempt to address this problem, the clustering-based method that utilizes crowding distance (CD) technique to balance the optimality of the objectives in Pareto optimal solution search is proposed. …”
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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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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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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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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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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks 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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Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation by Mahesh, K., Nallagownden, P., Elamvazuthi, I.

“…Moreover, the results of proposed method are validated with other optimization algorithms as reported by others in the literature. …”
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