concept

Cuckoo Search

Also known as: CS, Cuckoo Search, cuckoo search algorithm, Cuckoo optimization algorithm

Facts (15)

Sources

Demand side management using optimization strategies for efficient ... journals.plos.org PLOS ONE Mar 21, 2024 12 facts

claimThe 'Fixed Egg Laying Radius' in the Cuckoo Search algorithm represents the neighborhood area around a solution where new solutions, referred to as eggs, are generated.

referenceThe Cuckoo Search (CS) algorithm, developed by Xin-She Yang and Suash Deb in 2009, is inspired by the obligate brood parasitism of certain cuckoo species, where cuckoos lay eggs in the nests of host birds.

claimV. MK, Chokkalingam B, and S. D. utilized several optimization strategies to construct objective functions for their Demand Side Management algorithm, including the Bat Optimization Algorithm (BOA), African Vulture Optimization (AVOA), Cuckoo Search Algorithm, Chaotic Harris Hawk Optimization (CHHO), Chaotic-based Interactive Autodidact School (CIAS) algorithm, and Slime Mould Algorithm (SMA).

procedureThe optimization algorithms (BOA, AVOA, CS, CHHO, CIAS, and SMA) were evaluated on a high-performance Intel i7 13th gen 1335 processor with 16 GB RAM to determine the best method in terms of result and speed.

referenceYang X.-S. authored the chapter 'Cuckoo Search' in the book 'Nature-Inspired Optimization Algorithms', published by Elsevier in 2014.

codeAlgorithm: Cuckoo Search for Demand Side Management Input: Number of nests N, Discovery rate Pa, Max generations Genmax Output: Principal Cuckoo Nest Position for Peak Load Reduction 1: Initialize nests Xi randomly for i = 1 to N 2: Evaluate the fitness of each nest 3: while (gen < Genmax) do 4: Get a cuckoo (i.e., solution) randomly by Lévy flights 5: Choose a nest j randomly and evaluate its fitness 6: if (fitness (Xi) > fitness (Xj)) then 7: Replace j with the new solution Xi 8: end if 9: Abandon a fraction Pa of worse nests and build new ones 10: Keep the best solutions (nests) and perform local searches 11: Rank the nests and find the current best 12: gen = gen + 1 13: end while 14: Output the best nest which is the DSM schedule

claimThe Cuckoo Search (CS) algorithm is recognized for its fast convergence in global optimization challenges for demand-side management.

measurementThe Cuckoo Search algorithm operates Demand Side Management with a peak load of 4.6MW for residential loads and 3MW for IT sector loads.

procedureThe Cuckoo Search algorithm for Demand Side Management (DSM) proceeds in the following steps: (1) Initialization: Generate initial nests, each representing a DSM schedule. (2) Fitness Evaluation: Calculate the fitness of each nest based on the peak load (Dpeak) for its DSM schedule. (3) Loop Until Convergence: For each generation, generate a new solution (Xi) using Lévy flights for a randomly chosen cuckoo, choose a nest randomly and compare its fitness with (Xi), apply a discovery rate (Pa) to determine if eggs are discovered (if discovered, the nest is abandoned and a new one is built), retain the best nests and perform local searches, abandon a fraction (Pa) of worse nests and build new ones via Lévy flights, rank the nests to find the best, and terminate if maximum generations or convergence criteria are met.

procedureThe Cuckoo Search algorithm utilizes two primary behaviors: (1) Lévy Flights, a type of random walk used for global exploration to search large spaces, and (2) Discovery Rate (Pa), which represents the probability of a host bird discovering a cuckoo egg, analogous to the rate of local exploitation in the search space.

imageFigure 12 displays the load profile curve achieved from Demand Side Management using the Cuckoo Search algorithm.

referenceThe study utilizes several optimization algorithms to construct objective functions for Demand Side Management (DSM), including the Bat Optimization Algorithm (BOA), African Vulture Optimization Algorithm (AVOA), Adaptive Neuro-Fuzzy Inference System (ANFIS), Cuckoo Search (CS) Algorithm, Chaotic Harris Hawk Optimization (CHHO), Chaotic-based Interactive Autodidact School (CIAS) algorithm, and the Slime Mould Algorithm (SMA).

A comprehensive overview on demand side energy management ... link.springer.com Springer Mar 13, 2023 2 facts

claimIn the context of energy management optimization, COA stands for Cuckoo optimization algorithm.

referenceLiping L, Ning W, and Peijun Z published 'Modified cuckoo search algorithm with variational parameters and logistic map' in MDPI in 2018.

A critical review on techno-economic analysis of hybrid renewable ... link.springer.com Springer Dec 6, 2023 1 fact

referenceSanajaoba S and Fernandez E applied the Cuckoo Search algorithm for the optimal sizing of a remote compound renewable power system in 2016.