Network optimization uses mixed-integer linear programming (MIP-LP) modeling algorithms. Supply Chain Guru has a complete, flexible, and extremely powerful optimization engine which can solve the most difficult problems.
You can even customize the optimization through the addition of custom constraints and variables! Network optimization will evaluate millions of feasible network configurations and report the most profitable structure. [figure 2]
After simulating the network structure, you can use Guru's batch run capabilities and multiple scenario runs to improve the inventory levels, sourcing policies rules and transportation mode logic. [figure 3]
Once you've run a network optimization, Guru's automatic "Implement Optimized Network" tool will create a new scenario with only the optimal network included. You've optimized on cost, now evaluate the service rates, inventory levels, and holding costs of your optimal network. [figure 4]
In the first three steps, you optimized the network structure, simulated the base case optimal structure, then iterated to improve inventory levels, placement, and supply chain policy. In the last step of the methodology, you can use sensitivity analysis to establish the valid range of the selected design.
If fuel prices rise, is this still the best structure? If duties and tariffs are eliminated, would a different structure become a better alternative? How far would duties have to fall to change the answer?
New - Design your Supply Chain Network to account for Greenhouse Gas Emissions and determine its Carbon Footprint.
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