Incorporating uncertainty in optimal decision making: Integrating mixed integer programming and simulation to solve combinatorial problems
ABSTRACT We introduce a novel methodology that integrates optimization and simulation techniques to obtain estimated global optimal solutions to combinatorial problems with uncertainty such as those of facility location, facility layout, and scheduling. We develop a generalized mixed integer programming (MIP) formulation that allows iterative interaction with a simulation model by taking into account the impact of uncertainty on the objective function value of previous solutions. Our approach is generalized, efficient, incorporates the impact of uncertainty of system parameters on performance and can easily be incorporated into a variety of applications. For illustration, we apply this new solution methodology to the NP-hard multi-period multi-product facility location problem (MPP-FLP). Our results show that, for this problem, our iterative procedure yields up to 9.4% improvement in facility location-related costs over deterministic optimization and that these cost savings increase as the variability in demand and supply uncertainty are increased.
- Production Planning and Control 01/2002; 13(1):35-46. · 0.60 Impact Factor
- [show abstract] [hide abstract]
ABSTRACT: An important problem facing the manager of an outpatient health care clinic involves determining the best combination of services, facilities, and personnel to maximize profits and simultaneously achieve acceptable measures of the clinic's daily performance. This problem is often attacked using either linear programming or computer simulation. This paper uses a recursive optimization-simulation approach which takes advantage of the best features of both optimization and simulation while minimizing the disadvantages of each method used alone. Results from a hypothetical setting using data from several actual settings demonstrate the value of the recursive method.Decision Sciences 06/1979; 10(3):412 - 433. · 1.36 Impact Factor