Simulation--optimization has received a spectacular attention in the past decade. However, the theory still cannot meet the requirements from practice. Decision makers ask for methods solving a variety of problems with diverse aggregations and objectives. To answer these needs, the interchange of solution procedures becomes a key requirement as well as the development of (1) general modeling methodologies able to represent, extend and modify simulation--optimization as a unique problem, (2) mapping procedures between formalisms to enable the use of different tools. However, no formalism treats simulation--optimization as an integrated problem. This work aims at partially filling this gap by proposing a formalism based upon Event Relationship Graphs (ERGs) to represent the system dynamics, the problem decision variables and the constraints. The formalism can be adopted for simulation--optimization of control policies governing a queueing network. The optimization of a Kanban Control System is proposed to show the whole approach and its potential benefits.
['Andrea Matta', 'Giulia Pedrielli', 'Arianna Alfieri']
Event relationship graph lite: event based modeling for simulation-optimization of control policies in discrete event systems