Difference Between Simulation and Optimization

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Objectives Paragraph Uncertainty in the business environment is a major threat at each and every level of the supply chain. Every day new challenges and opportunities arise – rising cost of fue, implications of an organization’s carbon footprint, outsourcing regulations, tax incentives, and political fluctuation. Proactively monitoring the implications of such events at frequent intervals is crucial for an organization. By using a variety of Supply Chain modeling and mathematical tools, an organization is able to develop an understanding of the implications of such factors. However, the vast array of tools also creates a dilemma about the best modeling approach. In the field of supply chain modeling, one dilemma that a corporation faces…show more content…
Uncertainty of demand is incorporated by using statistical distributions, which eloquently represents a real world scenario. Simulation enables the decision maker to see the impact level of various day-to-day variables on the overall supply chain performance (e.g. identifying the weeks where the plant might face stock outs). Optimization always has an objective function such as cost minimization or revenue/profit maximization. In case of simulation, the focus is more on observing supply chain behavior over a period of time with the intent to identify the controlling factors of a system and their effect on future performance of a supply chain. Optimization tools focus on giving the best results under certain constraints, such as finding the optimal inventory level to meet a certain target service level. It gives the optimized operating variables as output. Simulation enables the user to vary a few variables at specific time bucket in the planning period of the modeled scenario. Simulation provides the flexibility of defining variables closer to real life, such as selecting a demand pattern from a wide range of available distribution such as Normal, Poisson, Beta, Max Extreme etc. Supply chain modeling can be further categorized into four segments based on the available alternatives and complexities of the
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