CS 286P Introduction to Optimization Class
Key Topics
CS 286P Introduction to Optimization
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Course Overview
This version of the course will focus on Discrete (Combinatorial) Optimization. Let's learn more about the programme. Combinatorial optimization is a branch of mathematics related to operations research and computational complexity.
The process of selecting the best object or combination of objects from a limited number of options is known as combinatorial optimization. Many of these problems are unsolvable by exhaustive search because the set is finite but cannot be identified. Common problems include the travelling salesman problem, the minimum spanning tree problem, and the knapsack problem. Real-world applications include airline operations, supply chain management, logistics, finance, healthcare, and environmental science and engineering.
Discrete optimization was the most powerful topic in the broader discipline of Operations Research prior to WWII (the official dates appear to be 1939-1945). The initial impetus was ballistics (in general).
Many technology companies have large optimization and operations research departments (Amazon, Uber, Didi). Smaller ones (Apple, Dell, Intel, and so on) may or may not be related to supply chain management.
Grading
The final grade will be determined by four individual homework assignments (40 per cent of the grade) and five group projects (50 per cent of the grade) (40 per cent for the first 4 and 20 per cent for the final project).
There will be no final exam at the conclusion of the course. The final assignment is due on December 10th, the day before the final exam. In case, you do not get the desirable output/result then we can help you in this too. You just need to ask us to take my online exam for me and we give you a guarantee of high grades.
Evaluation of Assignments
Group homework will be completed in groups of 2-4 students, with the majority of groups consisting of three students. However, in this course, you must form your own groups, or ask the TAs or Professor Regan for assistance if you are having difficulty finding a group.
In addition, latex should be used for written assignments (most students will use Overleaf). It is critical to remember that both the final individual homework assignment and the final project must be completed on time. However, in some cases, late homework is acceptable. However, we can help you with your assignments, we offer services like do my homework or do my assignment and assure you to boost your grades. Even you can ask us for hist 1302 united states history ii online coursework help.
References and Readings
- Combinatorial Optimization: Theory and Algorithms, by Bernhard Korte and Jens Vygen – this is available from the UCI library. Please download a copy of the whole book because we will occasionally have a reading assignment.
- A Tutorial on Integer Programming, Gerard Cornuejols, Michael J. Trick, Matthew J. Saltzman, widely available online and also in the course files.
- Optimization by Grasp by M.G.C. Resend and C.C. Riberio – this is available online from the UCI library. Please download a copy of the whole book because we will refer to it later.
- Morrison, D.R., Jacobson, S.H., Sauppe, J.J. and Sewell, E.C., 2016. Branch-and-bound algorithms: A survey of recent advances in searching, branching, and pruning. Discrete Optimization, 19, pp.79-102.
- Additional References will be added as the course progresses.
So this is all about the referencing and readings. You can take our help if you required it, we can help you with any sort of online coursework such as CJS 204.91C CIVIL LIBERTIES AND CIVIL RIGHTS Online Course, Online PearsonLab class, Strategic Management and policy online coursework and so on.
Coding and Optimization Solver Guidelines
Homework should be completed in Python or Matlab using Gurobi. If you are unable to write assignments in python or Matlab, you can seek assistance from our experts. They will assist you in the best way possible and will also assist you in gaining some additional knowledge.
This is the web link where you must register with the Gurobi for the work done.
https://www.gurobi.com/downloads/end-user-license-agreement-academic/
Course Schedule- Subject to minor changes as the course progresses
Week 1: Introduction to Optimization as a field, Introduction to current business application |
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Week 2: Introduction to Classical Problems in Discrete Optimization |
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Week 3: Tricks for formulating Integer Programming Problems |
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Week 4 |
Formulating Some Real Problems + Branch and Bound
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Week 5 |
More about solving integer linear programs via Branch and Bound
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Week 6: Extended vs Compact Formulations |
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Week 7: Column Generation: Basic |
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Week 8: Column Generation: Dual Stabilization |
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Weeks 9 and 10: Metaheuristics Revisited |
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