“…Since their introduction, G-networks have been extensively studied covering several extensions such as triggered movement, which redirect customers among the queues [15]; catastrophes or batch service [18], adders [19]; multiple classes of positive customers and signals [20], state-dependent service disciplines [21,22,23], tandem networks [24,25], deletion of a random amount of work [26,27], retrials [28,29] (not exhaustive list). For a complete bibliography see [30,31,32]. G-networks have been shown to be a diverse application tool to analyse and optimise the effects of dynamic load balancing in large scale networks [33] as well as in Gene Regulatory Networks [34,35].…”