MTM3691 – Theory of Linear Programming (Fall 2024-2025)
Instructor Information
Instructors: Hale Gonce Köçken (Gr. 2) and Gökhan Göksu (Gr. 4)
E-mail (HGK): hgonce [at] yildiz [dot] edu [dot] tr
E-mail (GG): gokhan [dot] goksu [at] yildiz [dot] edu [dot] tr
Course Web Site: gokhangoksu.github.io/MTM3691
General Information
Schedule: Monday, 09:00-12:00
Classroom: KMB-320
Office Hours: Monday, 13:00-16:00
Expectations and Goals
Course Materials
Tentative Course Schedule
Week 1 (30.09.2024): Linear Programming (LP) Problem: Definition, Two-Variable LP Model and Model Construction
[Slide]
Week 2 (07.10.2024): Properties of LP Model, Graphical Solution Method (Max/Min), LP Model in Equation Form, Transition from Graphical Solution to Algebraic Solution
[Slide]
Week 3 (14.10.2024): No Class
[No Class]
Week 4 (21.10.2024): Algebraic Method, Simplex Method: Optimality and Feasibility Conditions
[Slide]
Week 5 (28.10.2024, Online Session): Artificial Starting Solution: M-Method
[Slide]
Week 6 (04.11.2024): Special Cases in the Simplex Method: Degeneration, Alternative Optima, Unbounded Solution, Infeasible Solution
[Slide]
Week 7 (11.11.2024): Converting an LP to Standard Form: Lower/Upper/Range Bounded Variables, Free Variables
[Slide]
Week 8 (18.11.2024): Midterm I
[Midterm I]
Week 9 (25.11.2024): Optimality and Feasibility Conditions, Some Basic Theorems and their Proofs
[Slide]
Week 10 (02.12.2024): Sensitivity Analysis: Graphical and Algebraic
[Slide]
Week 11 (09.12.2024): Duality: Canonical Form, Primal-Dual Relations, Inverse Matrix, Optimal-Dual Solution
[Slide]
Week 12 (16.12.2024): Midterm II
[Midterm II]
Week 13 (23.12.2024): Dual Simplex Algorithm: Dual Feasibility and Optimality Conditions
[Slide]
Week 14 (30.12.2024): Transportation Problem (TP) and its Algorithm: Balancing the TP, Determining the Initial Solution
[Slide]
Week 15 (06.01.2025): Transportation Problem (TP) and its Algorithm: Determining the Initial Solution (Continued), Optimization Calculations of the TP Algorithm
[Slide]
Course Evaluation
Midterm I: 35 %
Midterm II: 25 %
Final: 40 %
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