Search Results - optimal ((((lbs algorithm) OR (acs algorithm))) OR (((_ algorithm) OR (new algorithm))))
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New heuristic function in ant colony system for the travelling salesman problem
Published 2012“…Ant Colony System (ACS) is one of the best algorithms to solve NP-hard problems.However, ACS suffers from pheromone stagnation problem when all ants converge quickly on one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic values to calculate the probability of choosing the next node. …”
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New heuristic function in ant colony system algorithm
Published 2012“…NP-hard problem can be solved by Ant Colony System (ACS) algorithm.However, ACS suffers from pheromone stagnation problem, a situation when all ants converge quickly to one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic value to calculate the probability of choosing the next node.However, the heuristic value is not updated throughout the process to reflect new information discovered by the ants.This paper proposes a new heuristic function for the Ant Colony System algorithm that can reflect new information discovered by ants.The credibility of the new function was tested on travelling salesman and grid computing problems.Promising results were obtained when compared to classical ACS algorithm in terms of best tour length for the travelling sales-man problem. …”
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Ant colony optimization in dynamic environments
Published 2010“…Apart from the size of the optimization problem, how the swapping interval affects the dynamic optimization by the ant algorithms is also investigated. …”
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Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…Pruning is the popular framework for preventing the dilemma of over fitting noisy data. This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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Evolutionary mating algorithm
Published 2023“…This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve constrained optimization problems. …”
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Modified ACS centroid memory for data clustering
Published 2019“…Ant Colony Optimization for Clustering (ACOC) is a swarm algorithm inspired from nature to solve clustering issues as optimization problems. …”
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Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy
Published 2023“…Decision making; Natural language processing systems; Bat algorithms; Heading policy; Multi-reservoir operation; Multi-reservoir systems; Optimization algorithms; Power- generations; Salp swarms; Seagull optimization algorithm; Swarm algorithms; Two-point; Optimization…”
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A New Near Optimal Harmonics Elimination PWM Algorithm For AC Traction Drives
Published 2002“…The paper presents an algorithm to calculate near optimal switching angles, which will permit a fast and efficient realization using a microprocessor. …”
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Applying DACS3 in the Capacitated Vehicle Routing Problem
Published 2010“…Ant Colony System (ACS) is a well known optimization algorithm to find a good route solution for logistics and transportation industries such as Traveling Salesman Problem (TSP) or Vehicle Routing Problem (VRP), for the company maximize the efficiency and resource. …”
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Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy
Published 2021“…To achieve this, the Two-Point Heading Rule was integrated with a new optimization algorithm, namely the Seagull Optimization Algorithm (SEOA). …”
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Interacted multiple ant colonies optimization framework: An experimental study of the evaluation and the exploration techniques to control the search stagnation
Published 2010“…Search stagnation is a serius prblem that all Ant Colony Optimization (ACO) algorithms suffer from regardless of their application domain. …”
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An improved leader particle swarm optimisation algorithm for solving flexible ac transmission systems optimisation problem in power system
Published 2014“…The results of applying improved leader PSO to IEEE 14 bus power system shows its significant outperformance over six other optimisation algorithms including conventional PSO, mutated PSO, enhanced PSO, harmony search,genetic algorithm and gravitational search algorithm. …”
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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method
Published 2023“…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”
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Development of control algorithm for a new 12s-6p single phase field excited flux switching motor
Published 2020“…In this research, two algorithms have been proposed in which first algorithm is based on bipolar DC signals while second algorithm is based on field oriented control (FOC) principle. …”
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An Efficient Improvement Of Ant Colony System Algorithm For Handling Capacity Vehicle Routing Problem
Published 2020“…The proposed study seeks to find the best solution of CVRP by using improvement ACS with the accompanying targets: (1) To decrease the distance as long distances negatively affect the course of the process since it consumes a great time to visit all customers. (2) To implement the improvement of ACS algorithm on new data from the database of CVRP. …”
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Improved prediction of daily pan evaporation using Bayesian Model Averaging and optimized Kernel Extreme Machine models in different climates
Published 2023“…Bayesian networks; Climate models; Forecasting; Knowledge acquisition; Machine learning; Particle swarm optimization (PSO); Uncertainty analysis; Water resources; Wind; Bayesian model averaging; Daily pan evaporation; Gamma test; Kernel extreme learning machine model; Learning machines; Machine modelling; Optimization algorithms; Uncertainty; Water planning; Water resources management; Evaporation; algorithm; Bayesian analysis; evaporation; machine learning; numerical model; optimization; stochasticity; uncertainty analysis…”
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Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization
Published 2018“…The main contribution of this paper is a new optimized AC scheduling approach that focuses on indoor thermal comfort using a new multi-objective optimization algorithm, called the improved global particle swarm optimization (IGPSO), which able to find better optimal solutions faster than its original version, the global particle swarm optimization (GPSO) algorithm. …”
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Review on Dam and Reservoir Optimal Operation for Irrigation and Hydropower Energy Generation Utilizing Meta-Heuristic Algorithms
Published 2023“…Biomimetics; Computational efficiency; Dams; Electric load dispatching; Heuristic algorithms; Heuristic methods; Hydroelectric power; Hydroelectric power plants; Irrigation; Mathematical programming; Scheduling; Structural design; Water distribution systems; Water resources; Water supply; Application problems; Hydro-power generation; Meta heuristic algorithm; Non-differentiability; Problem formulation; Reservoir optimal operation; Reservoir optimizations; Scientific discipline; Reservoirs (water)…”
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Hybrid evolutionary optimization algorithms: A case study in manufacturing industry
Published 2014“…Such complex problems of vagueness and uncertainty can be handled by the hybrid evolutionary intelligence algorithms. In this chapter, a new hybrid evolutionary optimization based methodology using a specific non-linear membership function, named as modified S-curve membership function, is proposed. …”
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