Solving location problems with simulation modelling — A case from the construction industry

Location problems are often solved by means of optimization. Simulation is often used to test the feasibility of an optimal solution after that the optimal solution is obtained. The test by simulation is done with more dynamic circumstances, introducing stochastic behavior. This research proposes to solve location problems directly in a simulation model, combining an optimization algorithm within the simulation model, thus providing solutions that are optimized in a stochastic and dynamic environment. The solution becomes more robust than an optimal solution provided by an optimization model. This methodology is tested on a real location problem in the construction industry, where a construction company is searching for the best location for their logistic distribution center. The location problem is modeled in Arena and solved with OptQuest. The suggested location method using simulation modeling solves the problem with nearly the same accuracy as an optimization model.