Formulate Jobshop Scheduling Problem & Determine Objective Function
Apply Constraints & Solve Mixed Integer Linear Programming Model
Obtain & Analyse Jobshop Schedule, Plot Schedule Gantt Charts
Welcome to "Job Shop Scheduling Using MILP Optimization on RStudio". This is a project-based course which should take under 2 hours to finish. Before diving into the project, please take a look at the course objectives and structure. By the end of this project, you will gain introductiory knowledge of Job Shop Scheduling, Mixed Integer Linear Programming (MILP), be able to use R Studio and lpSolveAPI library, formulate Jobshop scheduling problem as an optmisation problem & determine the objective function, apply constraints, run optimiser, obtain & analyse the solution. This course is at an intermediate level, and assumes knowledge of following: 1. Familiarity R language, including vectors, data frames, loops etc, and RStudio. 2. Linear Programming basics.
Mathematical Optimization
R Programming
Data Analysis
Job Shop Scheduling
Rstudio
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction & Load The Libraries
Formulate Jobshop Scheduling Problem
Apply The Makespan Constraint
Apply Precedence Constraints on Tasks
Apply No-Overlap Constraint on Tasks
Run Optimiser, Obtain & Analyse Solution
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
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Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
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