A genetic algorithm for joint optimization of capacity and flow assignment in packet switched networks

Mostafa, Mohamed; Eid, Saad

doi:10.1109/nrsc.2000.838928

Cited by 7 publications

(2 citation statements)

References 8 publications

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“…Investigators have applied GAs to the SP routing problem [5]- [7], multicasting routing problem [8], [9], ATM bandwidth allocation problem [10], capacity and flow assignment (CFA) problem [11], and the dynamic routing problem [12]. It is noted that all these problems can be formulated as some sort of a combinatorial optimization problem.…”

Section: A Review Of Ga-based Sp Algorithmsmentioning

confidence: 99%

A genetic algorithm for shortest path routing problem and the sizing of populations

Ahn

Ramakrishna

2002

IEEE Trans. Evol. Computat.

546

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Abstract-This paper presents a genetic algorithmic approach to the shortest path (SP) routing problem. Variable-length chromosomes (strings) and their genes (parameters) have been used for encoding the problem. The crossover operation exchanges partial chromosomes (partial routes) at positionally independent crossing sites and the mutation operation maintains the genetic diversity of the population. The proposed algorithm can cure all the infeasible chromosomes with a simple repair function. Crossover and mutation together provide a search capability that results in improved quality of solution and enhanced rate of convergence. This paper also develops a population-sizing equation that facilitates a solution with desired quality. It is based on the gambler's ruin model; the equation has been further enhanced and generalized, however. The equation relates the size of the population, the quality of solution, the cardinality of the alphabet, and other parameters of the proposed algorithm. Computer simulations show that the proposed algorithm exhibits a much better quality of solution (route optimality) and a much higher rate of convergence than other algorithms. The results are relatively independent of problem types (network sizes and topologies) for almost all source-destination pairs. Furthermore, simulation studies emphasize the usefulness of the population-sizing equation. The equation scales to larger networks. It is felt that it can be used for determining an adequate population size (for a desired quality of solution) in the SP routing problem.Index Terms-Gambler's ruin model, genetic algorithms, population size, shortest path routing problem.

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Section: A Review Of Ga-based Sp Algorithmsmentioning

confidence: 99%

A genetic algorithm for shortest path routing problem and the sizing of populations

Ahn

Ramakrishna

2002

IEEE Trans. Evol. Computat.

546

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“…Recently, Neural Networks (NNs), GAs, and other evolutionary algorithms have received a great deal of attention regarding their potential as optimization techniques for network design problems [2] [3] and are often used to solve many real world problems: the shortest path routing (SPR) problem [4]- [6], multicasting routing problem [4], ATM bandwidth allocation problem [7], capacity and flow assignment (CFA) problem [8], and the dynamic routing problem [9]. It is noted that all these problems can be formulated as some sort of a combinatorial optimization problem.…”

Section: Introductionmentioning

confidence: 99%

Priority-Based Genetic Algorithm for Shortest Path Routing Problem in OSPF

Lin

Gen

Studies in Computational Intelligence

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With the growth of the Internet, Internet service providers try to meet the increasing traffic demand with new technology and improved utilization of existing resources. Routing of data packets is the most important way to improve network utilization. Open Shortest Path First (OSPF) is the first widely deployed routing protocol that could converge a network in the low seconds, and guarantee loop-free paths. In this paper, we propose a new shortest path routing algorithm by using a priority-based Genetic Algorithm (priGA) approach in OSPF. Different with traditional Dijkstra's algorithms, GAs provide us great flexibility, robustness and adaptability to make efficient implementations for specific routing problems, such as Quality of Service (QoS) requirements, OSPF weight setting etc. Numerical experiments with various scales of network problems show the effectiveness and the efficiency of our approach by comparing with the recent researches.

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A genetic algorithm for joint optimization of capacity and flow assignment in packet switched networks

Cited by 7 publications

References 8 publications

A genetic algorithm for shortest path routing problem and the sizing of populations

A genetic algorithm for shortest path routing problem and the sizing of populations

Priority-Based Genetic Algorithm for Shortest Path Routing Problem in OSPF

Basic Network Models

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