Abstract

Decision-making in technological systems, such as communication networks, manufacturing facilities and supply chains, constitutes a common requirement able to lead companies galore to success or failure. This article presents a decision-making methodology, where the feasible structural configurations to be analysed are chosen heuristically in the frame of a single optimization problem. For stating the optimization problem and solving it efficiently, appropriate formalisms would be used. Compound Petri nets, a particular kind of parametric Petri nets, and alternatives aggregation Petri nets, are two Petri net–based formalisms able to integrate in the same model different alternative structural configurations. Moreover, even having different characteristics that might make them useful for different applications, both formalisms present common features, such as including a set of exclusive entities and the possibility of developing compact Petri net models, by the removal of redundant information. This article is also focused on the transformation algorithm between compound Petri nets and alternatives aggregation Petri nets. This algorithm is devoted to transform a model described by one of the formalisms into an equivalent model, that is, with the same behaviour, represented using the other formalism. Finally, several application examples are given for illustrating the steps of the transformation algorithm.

Highlights

  • Decision support systemsDecision support systems constitute tools of great help to the management of systems that show complex behaviour, arisen from the interrelations between the constituent subsystems

  • It has been shown how it is possible to relate two formalisms that have been created for representing a discrete event system (DES) with an undefined structure, by means of a transformation algorithm

  • Both formalisms, based on the paradigm of the Petri nets (PNs), the compound PNs and the aggregation Petri nets (AAPNs) share the possibility of removing redundant information in models built up from alternative PNs

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Summary

Introduction

Decision support systemsDecision support systems constitute tools of great help to the management of systems that show complex behaviour, arisen from the interrelations between the constituent subsystems. Application of a reduction rule to quasiidentical transitions, associated with different choice variables, obtaining an AAPN with a reduced set of transitions.

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