Department of Computer Science and Information Technology, College of Computer Science & Information Technology, Firat University, turkey

2020 ◽  
Vol 1 (1) ◽  
pp. 46-63
Author(s):  
Sam M. Alman
Keyword(s):  
Information Technology ◽  
Computer Science ◽  
Ant Colony Optimization ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Initial State ◽  
Science Field ◽  
Hard Problems ◽  
Technology College ◽  
Science Information

This paper provides uses a new Ant Colony based algorithms called U-Turning Ant colony optimization (U-TACO) for solving one of NP-Hard problems which is widely used in computer science field called Traveling Salesman Problem (TSP). U-Turning Ant colony Optimization based on making partial tour as an initial state for the basic Ant Colony algorithm. This paper provides tables and charts for the results obtained by U-Turning Ant colony Optimization for various TSP problems from the TSPLIB95.

scholarly journals U-Turning Ant Colony Algorithm for Solving Symmetric Traveling Salesman Problem

2018 ◽  
Vol 7 (4) ◽  
pp. 45
Author(s):  
Saman M. Almufti ◽  
Awaz A. Shaban
Keyword(s):  
Ant Colony Optimization ◽  
Traveling Salesman Problem ◽  
Ant Colony Algorithm ◽  
Traveling Salesman ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Initial State ◽  
Science Field ◽  
Np Hard Problem ◽  
Symmetric Traveling Salesman Problem

This paper provides a new Ant based algorithms called U-Turning Ant colony optimization (U-TACO) for solving a well-known NP-Hard problem, which is widely used in computer science field called Traveling Salesman Problem (TSP). Generally U-Turning Ant colony Optimization Algorithm makes a partial tour as an initial state for the basic conventional Ant Colony algorithm. This paper provides tables and charts for the results obtained by U-Turning Ant colony Optimization for various TSP problems from the TSPLIB95.

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.

Research on Application of Ant Colony Optimization

2014 ◽  
Vol 548-549 ◽  
pp. 1213-1216
Author(s):  
Wang Rui ◽  
Zai Tang Wang
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Ant Colony Algorithm ◽  
Optimal Algorithm ◽  
Convergence Speed ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Slow Convergence ◽  
Simulation Results ◽  
Research On Application

We research on application of ant colony optimization. In order to avoid the stagnation and slow convergence speed of ant colony algorithm, this paper propose the multiple ant colony optimization algorithm based on the equilibrium of distribution. The simulation results show that the optimal algorithm can have better balance in reducing stagnation and improving the convergence.

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