Cohort Intelligence: A Socio-inspired Optimization Method

Kulkarni, Anand J.; Krishnasamy, Ganesh; Abraham, Ajith

doi:10.1007/978-3-319-44254-9

Cited by 41 publications

(14 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For details refer to [18,21]. -Every candidate observes itself and every other candidate in the cohort to improve its individual behavior and associated qualities.…”

Section: Cohort Intelligence Algorithmmentioning

confidence: 99%

“…The probability-based constraint handling techniques was used to handle the constraints. Similar approach was also applied for solving real world combinatorial problems from healthcare and logistics domains and large sized complex problems from the Cross-Border Supply Chain domain [20], Traveling Salesman Problem (TSP) [21] and several benchmark problems [18]. A self-adaptive Cohort Intelligence (SACI) algorithm [22] was proposed using tournament mutation operator and a self-adaptive scheme to update the sampling interval.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimization of advanced manufacturing processes using socio inspired cohort intelligence algorithm

Kale

Pachpande

Naikwadi

et al. 2022

Int. J. Simul. Multidisci. Des. Optim.

View full text Add to dashboard Cite

The demand of Advanced Machining Processes (AMP) is continuously increasing owing to the technological advancement. The problems based on AMP are complex in nature as it consisted of parameters which are interdependent. These problems also consisted of linear and nonlinear constraints. This makes the problem complex which may not be solved using traditional optimization techniques. The optimization of process parameters is indispensable to use AMP's at its aptness and to make it economical to use. This paper states the optimization of process parameters of Ultrasonic machining (USM) and Abrasive water jet machining (AWJM) processes to maximize the Material Removal Rate (MRR) using a socio inspired Cohort Intelligent (CI) algorithm. The constraints involved with these problems are handled using static penalty function approach. The solutions are compared with other contemporary techniques such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Modified Harmony Search (HS_M) and Genetic Algorithm (GA).

show abstract

“…For details refer to [18,21]. -Every candidate observes itself and every other candidate in the cohort to improve its individual behavior and associated qualities.…”

Section: Cohort Intelligence Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of advanced manufacturing processes using socio inspired cohort intelligence algorithm

Kale

Pachpande

Naikwadi

et al. 2022

Int. J. Simul. Multidisci. Des. Optim.

View full text Add to dashboard Cite

show abstract

“…The cohort intelligence algorithm, proposed by Kulkarni et al, works on the selfsupervisory behavior of a group of candidates called a cohort, and has been found to be effective in solving unconstrained, as well as constrained problems [47]. A set of qualities leads to a particular behavioral characteristic.…”

Section: Algorithmmentioning

confidence: 99%

Optimal Fractional PID Controller for Buck Converter Using Cohort Intelligent Algorithm

Warrier

Shah

2021

ASI

View full text Add to dashboard Cite

The control of power converters is difficult due to their non-linear nature and, hence, the quest for smart and efficient controllers is continuous and ongoing. Fractional-order controllers have demonstrated superior performance in power electronic systems in recent years. However, it is a challenge to attain optimal parameters of the fractional-order controller for such types of systems. This article describes the optimal design of a fractional order PID (FOPID) controller for a buck converter using the cohort intelligence (CI) optimization approach. The CI is an artificial intelligence-based socio-inspired meta-heuristic algorithm, which has been inspired by the behavior of a group of candidates called a cohort. The FOPID controller parameters are designed for the minimization of various performance indices, with more emphasis on the integral squared error (ISE) performance index. The FOPID controller shows faster transient and dynamic response characteristics in comparison to the conventional PID controller. Comparison of the proposed method with different optimization techniques like the GA, PSO, ABC, and SA shows good results in lesser computational time. Hence the CI method can be effectively used for the optimal tuning of FOPID controllers, as it gives comparable results to other optimization algorithms at a much faster rate. Such controllers can be optimized for multiple objectives and used in the control of various power converters giving rise to more efficient systems catering to the Industry 4.0 standards.

show abstract

“…This algorithm mimicked the self-managed learning behavior of group candidates. So, supporting this concept Kulkarni et al [80] introduced Cohort Intelligence (CI) algorithm. The cohort advice to a group of candidates to collaborate and interact with each individual to accomplish personal goals which are shared with all.…”

Section: Cohort Intelligence Algorithmmentioning

confidence: 99%

Applicability and Efficiency of Socio-Cultural Inspired Algorithms in Optimizing Mechanical Systems – A Critical Review

Patel¹,

Kakandikar²,

Kulkarni³

2020

RCES

View full text Add to dashboard Cite

In the recent years' optimization algorithms are used in many real-life applications to get the best out of everything. There are many types of optimization algorithm such as Nature inspired algorithm, Bio-Inspired algorithm which also have their applications. This paper aims to presents different category of algorithms and their applications, which are inspired by the social behavior of humans in groups termed as family. These algorithms are widely appreciated by researchers from various domains for optimization. The performance of social algorithm (SA) to discover the global optimum solution for the constrained, unconstrained and multi-objective optimization problems is sound. This paper extensively reviews and presents the applicability and also efficiency of the socio-inspired algorithm in solving real life problems in the field of mechanical engineering mechanical engineering problems.

show abstract

Cohort Intelligence: A Socio-inspired Optimization Method

Cited by 41 publications

References 0 publications

Optimization of advanced manufacturing processes using socio inspired cohort intelligence algorithm

Optimization of advanced manufacturing processes using socio inspired cohort intelligence algorithm

Optimal Fractional PID Controller for Buck Converter Using Cohort Intelligent Algorithm

Applicability and Efficiency of Socio-Cultural Inspired Algorithms in Optimizing Mechanical Systems – A Critical Review

Contact Info

Product

Resources

About