Sourcing Decisions Become a Source of Cost Savings
Daryl Pereira 270002AW8D email@example.com | | Tags:  optimization ilogdialog
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Erica Klampfl of Ford Research & Advanced Engineering presented an overview of optimization efforts in the automotive industry during a time of increasing uncertainty, in fact downright “distress”, with many of their suppliers.
Using OPL, underpinned by CPLEX as the solving engine, she and her small team were able to meet an eight week deadline for novel analysis involving five separate phases of development. What amounts to a nonlinear Mixed Integer problem was decomposed into tractable portions, still of sizable dimension: a capacity submodel consisted of 1.69 million constraints and 852 thousand variables, while a utilization submodel had 1.78 million constraints and 8.48 million variables. This corresponds to 42 products, 229 requirements, 57 facilities, 37 processes, and 11 assembly plants. Three to four major iterations were required for convergence, requiring about 25 minutes per iteration (10 for capacity, 15 for utilization). Such modeling clearly is not for the faint of heart!
Why did they use these ILOG products? CPLEX’s reputation for solving large MIPs was a starting point. But performance tuning (barrier optimizer, etc) within OPL was important, as was overall ease of modeling setup time, and a facility for performing what-if studies. Perhaps the single biggest key was the need for an interface to Excel to bring the data into the modeling environment.
The results look compelling. The project confirmed the existence of excess capacity, it demonstrated a hub-and-spoke supply chain was optimal, and it identified the need for a new hub in southeastern Michigan. Overall five-year savings are estimated at $50 million, with $40 million of that up-front.