|
| Purpose | Results | Ref. |
|
| CSO applied on electrical payment system in order to minimize electricity cost for customers | CSO outperformed PSO | [46] |
| CSO applied on economic load dispatch (ELD) of wind and thermal generator | CSO outperformed PSO | [47] |
| BCSO applied on unit commitment (UC) | CSO outperformed LR, ICGA, BF, MILP, ICA, and SFLA | [48] |
| Applied CSO algorithm on UPFC to increase the stability of the system | IEEE 6-bus and 14-bus networks were used in the simulation experiments and desirable results were achieved | [49] |
| Applied ADCSO on reactive power dispatch problem to minimize active power loss | IEEE 57-bus system was used in the simulation experiments, in which ADCSO outperformed 16 other optimization algorithms | [50] |
| Applied CSO algorithm to regulate the position and control parameters of SVC and TCSC to improve available transfer capability (ATC) | IEEE 14-bus and IEEE 24-bus systems were used in the simulation experiments, in which the system provided better results after adopting CSO | [51] |
| Building a classification model based on BCSO and SVM to classify the transformers according to their reliability status. | The model performed better compared to a similar model, which was based on BPSO and VSM | [42] |
| Applied CSO to optimize the network structure and learning parameters of an ANN model named CPNN-CSO, which is used to predict household electric power consumption | CPNN-CSO outperformed ANFIS and similar methods with no CSO such as PNN and CPNN | [43] |
| Applied CSO and selective harmonic elimination (SHE) algorithm on current source inverter (CSI) | CSO successfully optimized the switching parameters of CSI and hence minimized the total harmonic distortion | [52] |
| Applied both CSO, PCSO, PSO-CFA, and ACO-ABC on distributed generation units on distribution networks | IEEE 33-bus and IEEE 69-bus distribution systems were used in the simulation experiments and CSO outperformed the other algorithms | [53] |
| Applied MCSO on MPPT to achieve global maximum power point (GMPP) tracking | MCSO outperformed PSO, MPSO, DE, GA, and HC algorithms | [54] |
| Applied BCSO to optimize the location of phasor measurement units and reduce the required number of PMUs | IEEE 14-bus and IEEE 30-bus test systems were used in the simulation. BCSO outperformed BPSO, generalized integer linear programming, and effective data structure-based algorithm | [55] |
| Used CSO algorithm to identify the parameters of single and double diode models in solar cell system | CSO outperformed PSO, GA, SA, PS, Newton, HS, GGHS, IGHS, ABSO, DE, and LMSA | [56] |
| Applied CSO and SVM to classify students’ facial expression | The results show 100% classification accuracy for the selected 9 face expressions | [39] |
| Applied CSO and SVM to classify students’ facial expression | The system achieved satisfactory results | [40] |
| Applied CSO-GA-PSOSVM to classify students’ facial expression | The system achieved 99% classification accuracy | [23] |
| Applied CSO, HCSO and ICSO in block matching for efficient motion estimation | The system reduced computational complexity and provided faster convergence | [16, 17, 57] |
| Used CSO algorithm to retrieve watermarks similar to the original copy | CSO outperformed PSO and PSO time-varying inertia weight factor algorithms | [58, 59] |
| Sabah used EHCSO in an object-tracking system to obtain further efficiency and accuracy | The system yielded desirable results in terms of efficiency and accuracy | [60] |
| Used BCSO as a band selection method for hyperspectral images | BCSO outperformed PSO | [61] |
| Used CSO and multilevel thresholding for image segmentation | CSO outperformed PSO | [62] |
| Used CSO and multilevel thresholding for image segmentation | PSO outperformed CSO | [63] |
| Used CSO, ANN and wavelet entropy to build an AUD identification system. | CSO outperformed GA, IGA, PSO, and CSPSO | [64] |
| Used CSO and FLANN to remove the unwanted Gaussian noises from CT images | The proposed system outperformed mean filter and adaptive Wiener filter. | [45] |
| Used CSO with L-BFGS-B technique to register nonrigid multimodal images | The system yielded satisfactory results | [65] |
| Used CSO in image enhancement to optimize parameters of the histogram stretching technique | PSO outperformed CSO | [66] |
| Used CSO algorithm for IIR system identification | CSO outperformed GA and PSO | [67] |
| Applied CSO to do direct and inverse modeling of linear and nonlinear plants | CSO outperformed GA and PSO | [68] |
| Used CSO and SVM for electrocardiograms signal classification | Optimizing SVM parameters using CSO improved the system in terms of accuracy | [38] |
| Applied CSO to increase reliability in a task allocation system | CSO outperformed GA and PSO | [69, 70] |
| Applied CSO on JSSP | The benchmark instances were taken from OR-Library. CSO yielded desirable results compared to the best recorded results in the dataset reference. | [71] |
| Applied BCSO on JSSP | ACO outperformed CSO and cuckoo search algorithms | [72] |
| Applied CSO on FSSP | Carlier, Heller, and Reeves benchmark instances were used, CSO can solve problems of up to 50 jobs accurately | [73] |
| Applied CSO on OSSP | CSO performs better than six metaheuristic algorithms in the literature. | [74] |
| Applied CSO on JSSP | CSO performs better than some conventional algorithms in terms of accuracy and speed. | [75] |
| Applied CSO on bag-of-tasks and workflow scheduling problems in cloud systems | CSO performs better than PSO and two other heuristic algorithms | [76] |
| Applied CSO on TSP and QAP | The benchmark instances were taken from TSPLIB and QAPLIB. The results show that CSO outperformed the best results recorded in those dataset references. | [77] |
| Comparison between CSO, cuckoo search, and bat-inspired algorithm to solve TSP problem | The benchmark instances are taken from STPLIB. The results show that CSO falls behind the other algorithms | [78] |
| Applied CSO and MCSO on workflow scheduling in cloud systems | CSO performs better than PSO | [79] |
| Applied BCSO on workflow scheduling in cloud systems | BCSO performs better than PSO and BPSO | [80] |
| Applied BCSO on SCP | BCSO performs better than ABC | [81] |
| Applied BCSO on SCP | BCSO performs better than binary teaching-learning-based optimization (BTLBO) | [82, 83] |
| Used a CSO as a clustering mechanism in web services. | CSO performs better than K-means | [84] |
| Applied hybrid CSO-GA-SA to find the overlapping community structures. | Very good results were achieved. Silhouette coefficient was used to verify these results in which was between 0.7 and 0.9 | [25] |
| Used CSO to optimize the network structures for pinning control | CSO outperformed a number of heuristic methods | [85] |
| Applied CSO with local search refining procedure to address high school timetabling problem | CSO outperformed genetic algorithm (GA), evolutionary algorithm (EA), simulated annealing (SA), particle swarm optimization (PSO) and artificial fish swarm (AFS). | [24] |
| BCSO with dynamic mixture ratios to address the manufacturing cell design problem | BCSO can effectively tackle the MCDP problem regardless of the scale of the problem | [86] |
| Used CSO to find the optimal reservoir operation in water resource management | CSO outperformed GA | [87] |
| Applied CSO to classify the the feasibility of small loans in banking systems | CSO resulted in 76% of accuracy in comparison to 64% resulted from OLR procedure. | [88] |
| Used CSO, AEM and RPT to build a groundwater management systems | CSO outperformed a number of metaheuristic algorithms in addressing groundwater management problem | [89] |
| Applied CSO to solve the multidocument summarization problem | CSO outperformed harmonic search (HS) and PSO | [90] |
| Used CSO and (RPCM) to address groundwater resource management | CSO outperformed a similar model based on PSO | [91] |
| Applied CSO-CS to solve VRPTW | CSO-CS successfully solves the VRPTW problem. The results show that the algorithm convergences faster by increasing population and decreasing cdc parameter. | [32] |
| Applied CSO and K-median to detect overlapping community in social networks | CSO and K-median provides better modularity than similar models based on PSO and BAT algorithm | [92] |
| Applied MOCSO, fitness sharing, and fuzzy mechanism on CR design | MOCSO outperformed MOPSO, NSGA-II and MOBFO | [93, 94] |
| Applied CSO and five other metaheuristic algorithms to design a CR engine | CSO outperformed the GA, PSO, DE, BFO and ABC algorithms | [95] |
| Applied EPCSO on WSN to be used as a routing algorithm | EPCSO outperformed AODV, a ladder diffusion using ACO and a ladder diffusion using CSO. | [33] |
| Applied CSO on WSN in order to solve optimal power allocation problem | PSO is marginally better for small networks. However, CSO outperformed PSO and cuckoo search algorithm | [96] |
| Applied CSO on WSN to optimize cluster head selection | The proposed system outperformed the existing systems by 75%. | [97] |
| Applied CSO on CR based smart grid communication network to optimize channel allocation | The proposed system obtains desirable results for both fairness-based and priority-based cases | [98] |
| Applied CSO in WSN to detect optimal location of sink nodes | CSO outperformed PSO in reducing total power consumption. | [99, 100] |
| Applied CSO on time modulated concentric circular antenna array to minimize the sidelobe level of antenna arrays and enhance the directivity | CSO outperformed RGA, PSO and DE algorithms | [101] |
| Applied CSO to optimize the radiation pattern controlling parameters for linear antenna arrays. | CSO successfully tunes the parameters and provides optimal designs of linear antenna arrays. | [102] |
| Applied Cauchy mutated CSO to make linear aperiodic arrays, where the goal was to reduce sidelobe level and control the null positions | The proposed system outperformed both CSO and PSO | [103] |
| Applied CSO and analytical formula-based objective function to optimize well placements | CSO outperformed DE algorithm | [104] |
| Applied CSO to optimize well placements considering oilfield constraints during development. | CSO outperformed GA and DE algorithms | [105] |
| CSO applied to optimize the network structure and learning parameters of an ANN model, which is used to predict an ASP flooding oil recovery index | The system successfully forecast the ASP flooding oil recovery index | [42] |
| Applied CSO to build an identification model to detect early cracks in beam type structures | CSO yields a desirable accuracy in detecting early cracks | [106] |
|
