Search Results - (( using functional study algorithm ) OR ( basic optimization _ algorithm ))

Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application by Hardhienata, Medria Kusuma Dewi, Priandana, Karlisa, Putra, Daffa Rangga, Sriatun, Mamiek, Wulandari, Buono, Agus, Mohamed, Raihani

“…By employing such a function, simulation results show that the total resource used by the agents and total communication cost can be optimized. …”
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Convergence Analysis of the African Buffalo Optimization Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad

“…This paper presents the convergence analysis of the newly-developed African Buffalo Optimization algorithm. African Buffalo Optimization is a simulation of the organizational skills of the African buffalos using two basic sounds: /waaa/ and /maaa/ as they transverse the African landscape in search of grazing pastures. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem by Mohd Said, Rahaini, A Aziz, Khairul Azha, Zainal Abidin, Amar Faiz, Mat Jizat, Jessnor Arif, Mohd Khairuddin, Ismail, Widiyanto, Sigit, Abdul Waduth, Mohamed Faisal

“…The Bat Algorithm's performance is evaluated using a case study from a database from Le2i Universite de Bourgoune. …”
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Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

“…Travelling salesman problem (TSP) is one the problems of NP-complete family, which means finding shortest complete close tour in the graph. This study seeks to solve this problem using Artificial Bee Colony (ABC) Algorithm along with the proposed Discrete Nearest Neighborhood Algorithm (DNNA). …”
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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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Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad by Mostafa, Modiri Delshad

“…Backtracking search algorithm (BSA) as the new evolutionary technique of optimization is used for solving the problems. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

“…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

“…The experimentations of the proposed algorithm are conducted using existing benchmark instances and a published case study on an energy-efficient job-shop model. …”
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Memoryless modified symmetric rank-one method for large-scale unconstrained optimization by Modarres, Farzin, Abu Hassan, Malik, Leong, Wah June

“…Problem statement: Memoryless QN methods have been regarded effective techniques for solving large-scale problems that can be considered as one step limited memory QN methods. In this study, we present a scaled memoryless modified Symmetric Rank-One (SR1) algorithm and investigate the numerical performance of the proposed algorithm for solving large-scale unconstrained optimization problems. …”
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Genetic algorithm optimization of product design for environmental impact reduction / Julirose Gonzales by Julirose , Gonzales

“…This dissertation presents a study on product design optimization which focuses on the inclusion of the potential environmental impact in the design consideration. …”
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Potential of data minimization techniques approach in improving DNA sequences alignment and comparison / Syed Abdul Mutalib Al Junid … [et al.] by Al Junid, Syed Abdul Mutalib, Haron, Muhammad Adib, Abd Majid, Zulkifli, Othman, Zulkifli

“…This study will initially involve algorithm modification, mathematical formulation, logic design and simulation for data minimization and existing DNA sequences alignment algorithm. …”
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Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan Yin Keong, Tan Yin

“…Having validated the model formulation and solution obtained, we believe that the model can be a useful basic tool to assist upper-level management in deciding on an optimal plan for crude oil production from an offshore operation. …”
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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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Implementation of Symmetric Rank-One Methods for Unconstrained Optimization by Khiyaban, Farzin Modarres

“…The rate of convergence of such algorithms are also discussed. Due to the presence of SR1 deciencies, we introduce a restarting procedure using eigenvalue of the SR1 update. …”
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Efficient beamforming and spectral efficiency maximization in a joint transmission LTE-A system by Faisal, Ali Raed

“…Moreover, addressing the lack-of-diversity issue in Basic Particle Swarm Optimization Algorithm (BPSOA) is a primary concern of this work. …”
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Catalytic conversion of methane and carbon dioxide in conventional fixed bed and dielectric barrier discharge plasma reactors by Istadi, Istadi

“…Moreover, the operating parameters, such as the CO2/CH4 feed ratio and reactor temperature, and the catalyst compositions, such as wt% CaO and wt% MnO, were optimized by using Weighted Sum of Squared Objective Functions algorithm. …”
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Model Identification Using Neuro-Fuzzy Approach by Lemma, T.A.

“…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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Model Identification Using Neuro-Fuzzy Approach by Lemma, T.A.

“…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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Optimal planning and design of hybrid renewable energy system for rural healthcare facilities / Olatomiwa Lanre Joseph by Olatomiwa Lanre , Joseph

“…Followed by development of prediction algorithm for solar radiation using soft-computing methodologies. …”
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