Multifactorial Evolutionary Algorithm for Inter-Domain Path Computation under Domain Uniqueness Constraint

被引:0
|
作者
Huynh Thi Thanh Binh [1 ]
Ta Bao Thangy [1 ]
Nguyen Binh Long [1 ]
Ngo Viet Hoang [1 ]
Pham Dinh Thanh [2 ]
机构
[1] Hanoi Univ Sci & Technol, Sch Informat & Commun Technol, Hanoi, Vietnam
[2] Tay Bac Univ, Fac Nat Sci & Technol, Son La, Vietnam
关键词
Multifactorial Evolutionary Algorithm; Inter-Domain Path Computation under Domain Uniqueness constraint; Path Computation Element; Evolutionary Algorithm; ARCHITECTURE;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Nowadays, connectivity among communication devices in networks has been playing a significant role, especially when the number of devices is increasing dramatically that requires network service providers to have a better architecture of management system. One of the popular approach is to divide those devices inside a network into different domains, in which the problem of minimizing path computation in general or Inter-Domain Path Computation under Domain Uniqueness constraint (IDPC-DU) problem in specific has received much attention from the research community. Since the IDPC-DU is NP-complete, an approximate approach is usually taken to tackle this problem when the dimensionality is high. Although Multifactorial Evolutionary Algorithm (MFEA) has emerged as an effective approximation algorithm to deal with various fields of problems, there are still some difficulties to apply directly MFEA to solve the IDPC-DU problem, i.e. different chromosomes may have different numbers of genes or to construct a feasible solution not violating the problem's constraint. Therefore, to overcome these limitations, MFEA algorithm with a new solution representation based on Priority-based Encoding is introduced. With the new representation of the solution, a chromosome consists of two parts: the first part encodes the priority of the vertex while the second part encodes information of edges in the solution. Besides, the paper also proposed a corresponding decoding method as well as novel crossover and mutation operators. Those evolutionary operators always produce valid solutions. For examining the efficiency of the proposed MFEA, experiments on a wide range of test sets of instances were implemented and the results pointed out the effectiveness of the proposed algorithm. Finally, the characteristics of the proposed algorithm are also indicated and carefully analyzed.
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页数:8
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