Techniques for bounding the convergence rate of genetic algorithms
Random Structures & Algorithms
Stochastic Network Interdiction
Operations Research
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
Minimizing a stochastic maximum-reliability path
Networks - Games, Interdiction, and Human Interaction Problems on Networks
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Deterministic network interdiction
Mathematical and Computer Modelling: An International Journal
Most vital links and nodes in weighted networks
Operations Research Letters
The k most vital arcs in the shortest path problem
Operations Research Letters
Vulnerability based robust protection strategy selection in service networks
Computers and Industrial Engineering
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In the literature, solution approaches to the shortest-path network interdiction problem have been developed for optimizing a single figure-of-merit of the network configuration when considering limited amount of resources available to interdict network links. This paper presents a newly developed evolutionary algorithm that allows approximating the optimal Pareto set of network interdiction strategies when considering bi-objective shortest path problems. Thus, the paper considers the concurrent optimization of two objectives: (1) maximization of shortest-path length and (2) minimization of interdiction strategy cost. Also, the paper considers the transformation of the first objective into the minimization of the most reliable path reliability. To solve these multi-objective optimization problems, an evolutionary algorithm has been developed. This algorithm is based on Monte Carlo simulation, to generate potential network interdiction strategies, graph theory to analyze strategies' shortest path or most reliable path and, an evolutionary search driven by the probability that a link will appear in the optimal Pareto set. Examples for different sizes of networks and network behavior are used throughout the paper to illustrate and validate the approach.