Advanced Solver Syllabus

Advanced Solver

This course covers Advanced Solver and consists of 21 topics.

Simplex LP Solver Model – In this video we show how the Simplex LP solver finds an optimal solution.
GRG Solver Model – In this video we show how the GRG solver finds an optimal solution to “smooth” nonlinear optimization problems.
Evolutionary Solver Model – In this video we show how the EVOLUTIONARY solver finds an optimal solution to “non-smooth” nonlinear optimization problems.
Locating One Warehouse – In this video we show how the GRG Solver optimally locates a single warehouse.
Locating Two Warehouses – In this video we show how the GRG Multistart Solver optimally locates two warehouses.
Assigning Workers to Jobs Part One – In this video we show how the Evolutionary Solver uses penalties to solve optimization problems using non-smooth functions such as IF and COUNTIF.
Assigning Workers to Jobs Part Two – This video is the conclusion of the previous example of Assigning Workers to Jobs.
Scheduling John Deere – In this video we show how John Deere used the Evolutionary Solver and the concept of target cell “penalties” to schedule the production of riding mowers.
Traveling Salesperson – In this video we show how the Evolutionary Solver is used to solve sequencing problems.
Estimating Elasticities – In this video we use the GRG Multistart solver to estimate product and cross product elasticities.
Advanced Learning Curve – In this video we show how to fit customized learning curve models.
Bin Packing Problem – In this video we show how to use the Evolutionary Solver to solve the classic Bin Packing Problem.
Final Exam Scheduling – In this video we use the Evolutionary Solver to determine a final exam schedule that eliminates student conflicts.
Discriminant Analysis – In this video we show how to use the Evolutionary Solver to develop a linear scoring rule that effectively classified data points into one of two groups.
Cluster Analysis – In this video we use the Evolutionary Solver to show that every US city is demographically similar to either LA, Memphis, SF, or Omaha.
Resolving Process Bottlenecks – In this video we use the evolutionary solver to find the minimum cost method of providing sufficient process capacity to meet demand.
The Toyota Manufacturing Sequence Algorithm – In this video we use the DIF capabilities of the Evolutionary Solver to implement the Toyota goal chasing method for scheduling car production.
Fast Food Scheduling – In this video we show how to use the Evolutionary Solver to schedule high school workers at a fast food restaurant
Solving Logic Puzzles Part One – In this video we use the Evolutionary Solver to solve two difficult logic puzzles.
Facility Layout – In this video we show how to locate hospital departments to minimize distance traveled.
Solving Logic Puzzles Part Two – In this video we use the Evolutionary Solver to solve two more difficult logic puzzles.
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