Preliminary review on analytical railway optimization models was undertaken by Assad [1].
We investigate the advantages of the hybrid analytical and simulation modeling approach, as compared to the traditional individual optimization methods with empirical tests, using a set of 3 methods, i.e., 1. Analytical model, 2. Simulation-based optimization model with OptQuest, and 3. Hybrid analytical and simulation modeling approach.
This is similar to the analytical result that the optimization model always has a lower facility congestion.
The termination criteria control the mechanism between the analytical model and the simulation optimization model.
We compare the proposed hybrid approach with the traditional analytical model and simulation-based optimization model to understand their differences along with their advantages and disadvantages in a practical decision making context by presenting our findings with computational analysis.
Taking the new production levels of the plants from the second iteration from the analytical model, the simulation-based optimization model is then run again to obtain a new solution of the TSLs of the warehouses, distribution centers, and retailers under uncertainties (Step 4).
In this paper, we developed a framework to achieve these three tasks, applying an analytical hierarchy process, a dynamic optimization model, and an attribute based contingent valuation technique, respectively.
The termination criteria control the mechanism between the analytical model and the simulation-based optimization model.
Using a hybrid modeling approach, we intend to determine the best storage locations and capacities of the warehouses, distribution centers, and retailers by incorporating the effect of uncertainty into the decision making process where an analytical model and a simulation-based optimization model are used iteratively.
Indeed, one of originality and uniqueness of this study is using the information gathered from the BPMN analytical tool, for developing a mathematical optimization model aimed at planning the OR activities and determining, for each day and each OR, the set of patients scheduled for surgery.
