On Analytical Comparative Study Considering Quantified Learning Creativity Analogy versus Ant Colony Intelligence

CBEMS-18,DMCCIA-18,EHSSM-18,BLEIS-18,ICLTET-18 March 21-23, 2018 Istanbul (Turkey) ◽

10.17758/dirpub1.e0318015 ◽

2018 ◽

Keyword(s):

Comparative Study ◽

Ant Colony

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A comparative study of Multi-Objective Ant Colony Optimization algorithms for the Time and Space Assembly Line Balancing Problem

Applied Soft Computing ◽

10.1016/j.asoc.2013.06.014 ◽

2013 ◽

Vol 13 (11) ◽

pp. 4370-4382 ◽

Cited By ~ 32

Author(s):

Juan Rada-Vilela ◽

Manuel Chica ◽

Óscar Cordón ◽

Sergio Damas

Keyword(s):

Comparative Study ◽

Ant Colony Optimization ◽

Assembly Line ◽

Optimization Algorithms ◽

Assembly Line Balancing ◽

Ant Colony ◽

Line Balancing ◽

Multi Objective ◽

Assembly Line Balancing Problem ◽

Ant Colony Optimization Algorithms

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Comparative Study on Ant Colony Optimization (ACO) and K-Means Clustering Approaches for Jobs Scheduling and Energy Optimization Model in Internet of Things (IoT)

International Journal of Interactive Multimedia and Artificial Intelligence ◽

10.9781/ijimai.2020.01.003 ◽

2020 ◽

Vol 6 (1) ◽

pp. 107 ◽

Cited By ~ 9

Author(s):

Sumit Kumar ◽

Vijender Kumar-Solanki ◽

Saket Kumar Choudhary ◽

Ali Selamat ◽

Rubén Gonzalez-Crespo

Keyword(s):

Internet Of Things ◽

Comparative Study ◽

Ant Colony Optimization ◽

Optimization Model ◽

Energy Optimization ◽

Ant Colony

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Comparative study of Genetic Algorithm and Ant Colony Optimization algorithm performances for robot path planning in global static environments of different complexities

2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA) ◽

10.1109/cira.2009.5423220 ◽

2009 ◽

Cited By ~ 9

Author(s):

Nohaidda Binti Sariff ◽

Norlida Buniyamin

Keyword(s):

Genetic Algorithm ◽

Path Planning ◽

Comparative Study ◽

Ant Colony Optimization ◽

Optimization Algorithm ◽

Ant Colony ◽

Robot Path Planning ◽

Ant Colony Optimization Algorithm ◽

Robot Path

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A Comparative Study of Ant Colony Optimization and Reactive Search for Graph Matching Problems

Evolutionary Computation in Combinatorial Optimization - Lecture Notes in Computer Science ◽

10.1007/11730095_20 ◽

2006 ◽

pp. 234-246 ◽

Cited By ~ 8

Author(s):

Olfa Sammoud ◽

Sébastien Sorlin ◽

Christine Solnon ◽

Khaled Ghédira

Keyword(s):

Comparative Study ◽

Ant Colony Optimization ◽

Graph Matching ◽

Ant Colony ◽

Matching Problems

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Ant Colony Optimization, Genetic Programming and a hybrid approach for credit scoring: A comparative study

The 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2014) ◽

10.1109/skima.2014.7083391 ◽

2014 ◽

Cited By ~ 4

Author(s):

Rojin Aliehyaei ◽

Shamim Khan

Keyword(s):

Genetic Programming ◽

Comparative Study ◽

Ant Colony Optimization ◽

Credit Scoring ◽

Hybrid Approach ◽

Ant Colony

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A Comparative Study: Ant Colony Optimization Algorithm and Backtracking Algorithm for Sudoku Game

2020 International Seminar on Application for Technology of Information and Communication (iSemantic) ◽

10.1109/isemantic50169.2020.9234267 ◽

2020 ◽

Author(s):

Novrindah Alvi Hasanah ◽

Luthfi Atikah ◽

Darlis Herumurti ◽

Andhik Ampuh Yunanto

Keyword(s):

Comparative Study ◽

Ant Colony Optimization ◽

Optimization Algorithm ◽

Ant Colony ◽

Ant Colony Optimization Algorithm

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A Comparative Study on Genetic Algorithm and Ant Colony Optimization in Resource Location Optimization

2020 IEEE Symposium Series on Computational Intelligence (SSCI) ◽

10.1109/ssci47803.2020.9308224 ◽

2020 ◽

Author(s):

Hang Zhou ◽

Xiao-Bing Hu

Keyword(s):

Genetic Algorithm ◽

Comparative Study ◽

Ant Colony Optimization ◽

Ant Colony ◽

Resource Location ◽

Location Optimization

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Comparative Study of Privacy Preservation of Data in Hybrid Cloud of Combined Clustering and Geometric Data Perturbation Approach and Hybrid Ant Colony Optimization and Gravitational Search Algorithm

Communication Software and Networks - Lecture Notes in Networks and Systems ◽

10.1007/978-981-15-5397-4_4 ◽

2020 ◽

pp. 25-37

Author(s):

Sridhar Reddy Vulapula ◽

Srinivas Malladi

Keyword(s):

Comparative Study ◽

Ant Colony Optimization ◽

Privacy Preservation ◽

Search Algorithm ◽

Gravitational Search Algorithm ◽

Ant Colony ◽

Perturbation Approach ◽

Hybrid Cloud ◽

Data Perturbation ◽

Gravitational Search

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A Comparative Study of a Hybrid Ant Colony Algorithm MMACS for the Strongly Correlated Knapsack Problem

Advances in Science Technology and Engineering Systems Journal ◽

10.25046/aj030601 ◽

2018 ◽

Vol 3 (6) ◽

pp. 1-22 ◽

Cited By ~ 2

Author(s):

Wiem Zouari ◽

Ines Alaya ◽

Moncef Tagina

Keyword(s):

Comparative Study ◽

Knapsack Problem ◽

Ant Colony Algorithm ◽

Ant Colony ◽

Strongly Correlated

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Comparative study between elephant herding optimization (EHO) and U-turning ant colony optimization (U-TACO) in solving symmetric traveling salesman problem (STSP)

Journal of Advanced Computer Science & Technology ◽

10.14419/jacst.v8i2.29403 ◽

2019 ◽

Vol 8 (2) ◽

pp. 32 ◽

Cited By ~ 1

Author(s):

Saman M. Almufti ◽

Ridwan Boya Marqas ◽

Renas R. Asaad

Keyword(s):

Comparative Study ◽

Ant Colony Optimization ◽

Traveling Salesman Problem ◽

Ant Colony Algorithm ◽

Optimization Problems ◽

Search Algorithm ◽

Traveling Salesman ◽

Ant Colony ◽

Initial State ◽

Symmetric Traveling Salesman Problem

Swarm Intelligence is an active area of researches and one of the most well-known high-level techniques intended to generat, select or find a heuristic that optimize solutions of optimization problems.Elephant Herding optimization algorithm (EHO) is a metaheuristic swarm based search algorithm, which is used to solve various optimi-zation problems. The algorithm is deducted from the behavior of elephant groups in the wild. Were elephants live in a clan with a leader matriarch, while the male elephants separate from the group when they reach adulthood. This is used in the algorithm in two parts. First, the clan updating mechanism. Second, the separation mechanism.U-Turning Ant colony optimization (U-TACO) is a swarm-based algorithm uses the behavior of real ant in finding the shortest way be-tween its current location and a source of food for solving optimization problems. U-Turning Ant colony Optimization based on making partial tour as an initial state for the basic Ant Colony algorithm (ACO).In this paper, a Comparative study has been done between the previous mentioned algorithms (EHO, U-TACO) in solving Symmetric Traveling Salesman Problem (STSP) which is one of the most well-known NP-Hard problems in the optimization field. The paper pro-vides tables for the results obtained by EHO and U-TACO for various STSP problems from the TSPLIB95.

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