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Application Research of Artificial Fish Swarm Algorithm of in Conbinatorial Optimization Problems

Author: LeiJuan
Tutor: MaZuo
School: Xi'an University of Technology
Course: Pattern Recognition and Intelligent Systems
Keywords: Artificial Fish School Algorithm Combinatorial optimization problems Traveling Salesman Problem Job Shop Scheduling Problem
CLC: O224
Type: Master's thesis
Year: 2010
Downloads: 294
Quote: 3
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Abstract


Combinatorial optimization problem has a very wide range of applications in real life , and has a strong engineering representative , but optimized for solving very difficult solving combinatorial optimization problems mainly heuristic algorithm . Artificial fish swarm algorithm is a new kind of swarm intelligence optimization algorithms , the principle is simple , fast convergence , high accuracy . Recent years has been the widespread attention and application . The traveling salesman problem is a class of the most basic , the most typical combinatorial optimization problem , the processing method of genetic algorithms, particle swarm optimization , ant colony algorithm . The basic genetic algorithm is easy to fall into local optimum . The foraging behavior of artificial fish swarm algorithm is a global convergence on the basis of the behavior and the rear-end of the cluster behavior has further strengthened the global convergence of the algorithm . The ant colony algorithm to solve the traveling salesman problem there is a slow rate of convergence and parameter setting a great influence on the performance of the algorithm , the artificial fish swarm algorithm through example proves better than the convergence rate of the ant colony algorithm . And parameter setting , the artificial fish swarm algorithm parameters on the performance of the algorithm is not sensitive to the number of artificial fish as long as a reasonable choice is the key to improve the efficiency of the algorithm . Artificial fish swarm algorithm to solve the traveling salesman problem, and prove that artificial fish swarm algorithm convergence time of great advantage , convergence accuracy is also guaranteed . The job shop scheduling problem with constraints typical combinatorial optimization problem , artificial fish swarm algorithm to solve the job shop scheduling problem is not retrieved References . Encoding to solve the job shop scheduling problem has been the difficulty of the problem and one of the key , this paper, a new coding , coding a constraint . Multi- constraint and dynamic job shop scheduling problem will be solving the objective function is divided into four situations , solve solving the objective function and constraints . Calculation examples of artificial fish swarm algorithm to solve the job shop scheduling problem with the existing literature has higher convergence speed and accuracy .

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CLC: > Mathematical sciences and chemical > Mathematics > Operations Research > Optimization of the mathematical theory
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