Reliable Communication Network Design with Evolutionary Algorithms

For the reliable communication network design (RCND) problem links are unreliable and for each link several options are available with different reliabilities and costs. The goal is to find a cost-minimal communication network design that satisfies a pre-defined overall reliability constraint. This paper presents two new EA approaches, LaBORNet and BaBORNet, for the RCND problem. LaBORNet uses an encoding that represents the network topology as well as the used link options and repairs infeasible solutions using an additional repair heuristic (CURE). BaBORNet encodes only the network topology and determines the link options by using the repair heuristic CURE as a local search method. The experimental results show that the new EA approaches using repair heuristics outperform existing EA approaches from the literature using penalties for infeasible solutions and find better solutions for existing problems from the literature as well as for new and larger test problems.