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Journal ArticleDOI

A comprehensive study of cuckoo-inspired algorithms

TLDR
Some of their important and emerging studies are discussed, their applications in several fields are investigated, and the differences between both algorithms are clarified so as to remove confusion between them.
Abstract
Nature-inspired metaheuristic algorithms are considered as the most effective techniques for solving various optimization problems. This paper provides a briefly review of the key features of the cuckoo-inspired metaheuristics: cuckoo search (CS) and cuckoo optimization algorithm (COA). In addition, it discusses some of their important and emerging studies, investigates their applications in several fields, and finally clarifies the differences between both algorithms so as to remove confusion between them.

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Citations
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Journal ArticleDOI

An enhanced associative learning-based exploratory whale optimizer for global optimization

TL;DR: It is argued that the exploitation tendency of WOA is limited and can be considered as one of the main drawbacks of this algorithm, and the exploitative and exploratory capabilities of modified WOA in conjunction with a learning mechanism are improved.
Journal ArticleDOI

A modified nature inspired meta-heuristic whale optimization algorithm for solving 0–1 knapsack problem

TL;DR: An improved whale optimization algorithm for solving both single and multidimensional 0–1 knapsack problems with different scales by adding a penalty function to the evaluation function so that the fitness of the feasible solutions can outperform the Fitness of the infeasible ones.
Journal ArticleDOI

A comprehensive review of quadratic assignment problem: variants, hybrids and applications

TL;DR: QAP is NP-hard problem that is impossible to be solved in polynomial time when the problem size increases, hence heuristic and metaheuristic approaches are utilized for solving the problem instead of exact approaches because these approaches achieve quality in the solution in short computation time.
Journal ArticleDOI

An improved cuckoo search algorithm for scheduling jobs on identical parallel machines

TL;DR: This paper proposes an improved cuckoo search algorithm (ICSA) to minimize makespan for the identical parallel-machine scheduling problem and presents a heuristic procedure based on the pairwise exchange neighborhood to produce smart cuckoos in the proposed ICSA.
Journal ArticleDOI

Krill herd algorithm based on cuckoo search for solving engineering optimization problems

TL;DR: The experimental results have proven that CSKH algorithm is well capable of solving constrained engineering design problems more efficiently and effectively than the basic CS and KH algorithm.
References
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Proceedings ArticleDOI

Particle swarm optimization

TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Book

Adaptation in natural and artificial systems

TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Journal ArticleDOI

Particle swarm optimization

TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
Proceedings ArticleDOI

Cuckoo Search via Lévy flights

TL;DR: A new meta-heuristic algorithm, called Cuckoo Search (CS), is formulated, based on the obligate brood parasitic behaviour of some cuckoo species in combination with the Lévy flight behaviour ofSome birds and fruit flies, for solving optimization problems.
Journal ArticleDOI

GSA: A Gravitational Search Algorithm

TL;DR: A new optimization algorithm based on the law of gravity and mass interactions is introduced and the obtained results confirm the high performance of the proposed method in solving various nonlinear functions.
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