Search Results - parallel (evolution OR solution) search algorithm

Parallel Homologous Search With Hirschberg Algorithm: A Hybrid MPI-Pthreads Solution. by Abdul Rashid, Nur'Aini, Abdullah, Rosni, Hj. Talib, Abdullah Zawawi

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Parallel metaheuristic algorithm for route planning using CUDA by Looi, Daniel Jun Jie

“…Area of Study: Massively Parallel Computing, Combinatorial Optimization Keywords: Parallel Metaheuristic Algorithm, Travelling Salesman Problem, CUDA, GPU, Genetic Algorithm…”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…Unlike existing OBL-based techniques, the PMT generates more than one candidate in multiple solution-space directions. To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

“…It is a series of activities based on the searching algorithm in order to access the best solutions. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

“…Unlike existing OBL-based techniques, the PMT generates more than one candidate in multiple solution-space directions. To evaluate the PMT's performance and adaptability, the PMT has been applied to four contemporary meta-heuristic algorithms, differential evolution (DE), particle swarm optimization (PSO), simulated annealing (SA), and whale optimization algorithm (WOA), to solve 15 well-known benchmark functions. …”
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Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm by Khoo, Thau Soon

“…Our algorithm uses non-fitness evolutionary distributed parallelized adaptive large neighbourhood search (NEDPALNS). …”
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A tabu search approach for mixed-model parallel assembly line balancing problem (type II) by Esmaeilian, Gholam Reza, Sulaiman, Shamsuddin, Ismail, Napsiah, Hamedi, Maryam, Megat Ahmad, Megat Mohammad Hamdan

“…Firstly, an initial solution is determined by a heuristic algorithm. Secondly, an optimum cycle time for each line in the mixed-model parallel assembly line (MMPAL) is calculated through the TS. …”
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Parallel multiple tabu search for multiobjective Urban Transit Scheduling Problem by Uvaraja, Vikneswary, Lai, Soon Lee, Abd Rahmin, Nor Aliza, Hsin, Vonn Seow

“…A set covering model was then adopted to minimize the number of buses and drivers simultaneously. A parallel tabu search algorithm was proposed to solve the problem by modifying the initialization process and incorporating intensification and diversification approaches to guide the search effectively from the different feasible domain in finding optimal solutions with lesser computational effort. …”
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Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network by Abduh Kaid, Monir Abdullah

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Multi-start local search for online scheduling in parallel operating theatre by Alimin, Nur Neesha, Abd Rahmin, Nor Aliza, Ibragimov, Gafurjan, Mohamed Ali, Nazihah

“…A modification of the local search algorithm was performed to improve the solutions and it is called multi-start local search (MSLS). …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…However, the current meta-heuristic algorithms do not ensure an optimum solution within a reasonable time. …”
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Accounting Information Systems Genetic Algorithms for All-Optical Shared Fiber-Delay-Line Packet Switches by Liew, S.Y., Wong, E.S.K.

“…In the first algorithm, packet scheduling is formulated as a tree-searching problem. …”
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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

“…Then, it started to find the best sequence of jobs for each line based on the generated population by heuristic algorithm. By this means, intelligence based genetic algorithm only concentrated on those initial populations that produce better solutions instead of probing the entire search space. …”
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Optimal placement of static VAR compensator using genetic algorithms by Mustafa, Mohd. Wazir, Wong, Yan Chiew

“…Genetic Algorithms (GAs) are stochastic searching algorithms that make the searching process jumps randomly from point to point, thus allowing escape from the local optimum, and search for many sub-optimum points in parallel.This paper presents an evolutionary computation algorithm for enhancing voltage stability. …”
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Single and Multiple variables control using Tree Physiology Optimization by Halim, A.H., Ismail, I.

“…In the proposed method, each shoot from each branch search for possible solution in parallel and the fitness is evaluated based on all best values found by branch search. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Development of a heuristic procedure for balancing mixed-model parallel assembly line type II by Esmaeilian, Gholamreza

“…The main advantages of employing TS are using a flexible memory structure during the search process, and intensification and diversification strategies, which help to make a comprehensive search in the solution space. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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A hybrid genetic algorithm for optimization of scheduling workflow applications in heterogeneous computing systems by Ahmad, S.G., Liew, Chee Sun, Munir, E.U., Ang, Tan Fong, Khan, S.U.

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