Iterative optimization and simulation of barge traffic on an inland waterway

We describe an iterative technique between optimization and simulation models used to determine solutions to optimization problems and ensure that the solutions are feasible for real world operations (in terms of a simulation model). The technique allows for the development of separate optimization and simulation models with varying levels of detail in each model. The results and parameters of the optimization model are used as input to the simulation model. The performance measures from the simulation output are compared to acceptable levels. These performance measures are then used to modify the optimization model if the simulation results are not acceptable. This iterative approach continues until an acceptable solution is reached. This iterative technique is applied to barge traffic on an inland waterway as an example. Linear programming is used as the optimization technique for the example while a simulation model is developed using Arena software.

1 Introduction

Simulation and optimization techniques are commonly applied in tandem to study many types of real world problems. Both simulation and optimization are applied to the same problem mainly for two reasons. First, it allows an analyst to simulate a specific system and then determine the optimal value for some parameter within the problem through the application of an optimization technique. An example of this is the OptQuest optimizer within Arena. It allows a specific simulated system to be optimized to determine the optimal values for a set of specified parameters. Various other techniques can be used to optimize specific parameters within a simulation model. Extensive examples and methodologies of the optimization of simulation models are available. Fu (2000), Swisher et al. (2000), Glover (1999), and Azadivar (1999) all presented various techniques at previous Winter Simulation Conferences. Secondly, simulation is often applied to the results of an optimization problem in order to check the validity of the model and/or the results. The results of the optimization model are used as inputs to the simulation model.