Hybrid Swarm Intelligence

Gonsalves, Tad

doi:10.4018/978-1-4666-5888-2.ch018

Cited by 8 publications

(4 citation statements)

References 35 publications

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“…In hybrid approaches, the main purposes are to achieve better optimization results, faster similar optimization results, and faster and better optimization results by the combination of methods such as global search, local search, convergence rate, and insensitivity to initial conditions [30]. In accordance with these objectives, the hybrid method called global-local search hybrids [31,32], in which one of the heuristic algorithms searches globally and the other locally, was used in this study to combine the standard GSA and TLBO.…”

Section: The Proposed Methods (Hybrid Gsa-tlbo)mentioning

confidence: 99%

A new hybrid gravitational search-teaching-learning-based optimization method for the solution of economic dispatch of power systems

Tefek¹,

Uğuz²

2019

Turk J Elec Eng & Comp Sci

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The economic dispatch problem (EDP) is a complex, constrained, and nonlinear optimization problem. In the EDP, the active power bus should operate between the minimum and maximum bus limits to minimize the fuel cost. In this study, a fast, efficient, and reliable hybrid gravitational search algorithm-teaching learning based optimization (GSA-TLBO) method was proposed for the purpose of solving the EDP in power systems. The proposed method separates the search space into two sections as global and local searching. In the first part, searching was carried out by GSA method effectively to form the second search space. In the second part, the optimum solution was sought in the local search space by the TLBO method. The proposed method was implemented to a constrained benchmark G01 problem. The proposed hybrid method was then applied to the constrained EDP in IEEE 30-bus and IEEE 57-bus test systems and Turkey's 22-bus power system to minimize the fuel cost. Obtained results were compared with other methods. Experimental results show that the proposed method results in shorter, more reliable, and efficient lowest fuel cost solutions. It has been found that the proposed method can be used to solve constrained optimization problems.

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Section: The Proposed Methods (Hybrid Gsa-tlbo)mentioning

confidence: 99%

A new hybrid gravitational search-teaching-learning-based optimization method for the solution of economic dispatch of power systems

Tefek¹,

Uğuz²

2019

Turk J Elec Eng & Comp Sci

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“…They are general-purpose but rather smart algorithms that scan the search space intelligently with techniques called the exploration and the exploitation phases. Metaheuristic algorithms can be applied to any problem with almost no restrictions, where the primary aim is to reach to the global optimum [1]- [3]. Nevertheless, researchers are putting dedicated and continuing efforts to improve the solution accuracy, ease of programming, faster convergence rate, flexibility, and so on when solving optimization problems.…”

Section: Introduction a Motivation And Research Gapmentioning

confidence: 99%

The Hybrid Harris Hawks Optimizer-Arithmetic Optimization Algorithm: A New Hybrid Algorithm for Sizing Optimization and Design of Microgrids

Çetinbaş¹,

Tamyürek²,

Demirtaş

2022

IEEE Access

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“…Problems in domain of business could be used by adoption and inventive usage of PSO algorithm (Olson, 2011;Rajesh 2013;Xing, 2014a). Besides optimization for neural networks in domain of business, PSO are also used as learning optimization tool in domain of engineering, environmental science, social science (Clerk, 2013;Olson, 2011, Russel, 2001Gonsalves, 2015).…”

Section: Introductionmentioning

confidence: 99%

Customer Profiling in Complex Analytical Environments Using Swarm Intelligence Algorithms

Klepac

2016

International Journal of Swarm Intelligence Research

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Customer profiling is always an interesting task from perspective of business. It became even bigger challenge in situation of complex analytical environment. Complex analytical environment can be caused by multiple modality of output variable as well as from big data environment, which cause data complexity in way of data quantity. As an illustration of presented concept particle swarm optimization algorithm will be used as a tool, which will find profiles from developed predictive model of neural network. Presented methodology has practical value for decision support in business, where information about customer profiles which prefers to buy some product or group products are valuable information for campaign planning and customer portfolio management.

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Hybrid Swarm Intelligence

Cited by 8 publications

References 35 publications

A new hybrid gravitational search-teaching-learning-based optimization method for the solution of economic dispatch of power systems

A new hybrid gravitational search-teaching-learning-based optimization method for the solution of economic dispatch of power systems

The Hybrid Harris Hawks Optimizer-Arithmetic Optimization Algorithm: A New Hybrid Algorithm for Sizing Optimization and Design of Microgrids

Customer Profiling in Complex Analytical Environments Using Swarm Intelligence Algorithms

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