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

2006 ◽  
pp. 234-246 ◽  
Author(s):  
Olfa Sammoud ◽  
Sébastien Sorlin ◽  
Christine Solnon ◽  
Khaled Ghédira
Keyword(s):  
Comparative Study ◽  
Ant Colony Optimization ◽  
Graph Matching ◽  
Ant Colony ◽  
Matching Problems

High-order graph matching based on ant colony optimization

2019 ◽  
Vol 328 ◽  
pp. 97-104 ◽  
Author(s):  
Yue Wu ◽  
Maoguo Gong ◽  
Wenping Ma ◽  
Shanfeng Wang
Keyword(s):  
Ant Colony Optimization ◽  
Graph Matching ◽  
High Order ◽  
Ant Colony

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

2019 ◽  
Vol 8 (2) ◽  
pp. 32 ◽  
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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