A genetic algorithm for the maximum edge-disjoint paths problem

作者：Hsu Chia Chun^*; Cho Hsun Jung

来源：Neurocomputing, 2015, 148: 17-22.

DOI：10.1016/j.neucom.2012.10.046

• Edge-disjoint paths
• MEDP
• Genetic algorithm
• Ant colony optimization
• Disjoint paths

Optimization problems concerning edge-disjoint paths have attracted considerable attention for decades. These problems have a lot of applications in the areas of call admission control, real-time communication, VLSI (Very-large-scale integration) layout and reconfiguration, packing, etc. The maximum edge-disjoint paths problem (MEDP) seems to lie in the heart of these problems. Given an undirected graph G and a set of I connection requests, each request consists of a pair of nodes, MEDP is an NP-hard problem which determines the maximum number of accepted requests that can be routed by mutually edge-disjoint (s(i),t(i)) paths. We propose a genetic algorithm (GA) to solve the problem. In comparison to the multi-start simple greedy algorithm (MSGA) and the ant colony optimization method (ACO), the proposed GA method performs better in most of the instances in terms of solution quality and time.

• 出版日期2015-1-19