An executable modelling and simulation framework for NP‐complete complexity problems and different forms of uncertainties

With rapid globalisation and increasing complexity of processes in service systems, there is need for a new and executable modelling framework that can be used to model, simulate and analyse the complex processes. The target processes often belong to the class of problems that are NP‐complete. Existing frameworks for modelling NP‐complete problems have certain limitations. A new Petri Net‐based framework, Fuzzy Coloured Petri Net with stochastic time delay and NP‐complete cases (FCPN‐std/NPC), is presented in this paper that allows modelling, simulation and analysis of processes that have an underlying NP‐complete complexity problem. The framework has the ability to characterise two types of uncertainties, variance type uncertainty and ambiguity type uncertainty. A new set of process‐semantics‐based nodes and mapping functions are defined for the FCPN‐std/NPC framework that allows modelling of a class of NP‐complete problems. A small supply chain example is used to illustrate the operational characteristics of the framework.