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.



Job Shop Scheduling Using MILP Optimization on RStudio

Instructor: Moses Gummadi
Access provided by Orascom Construction
Recommended experience
What you'll learn
- Formulate Jobshop Scheduling Problem & Determine Objective Function 
- Apply Constraints & Solve Mixed Integer Linear Programming Model 
- Obtain & Analyse Jobshop Schedule, Plot Schedule Gantt Charts 
Skills you'll practice
Details to know

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About this Guided Project
Learn step-by-step
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 
Recommended experience
1. Familiarity R language, including vectors, data frames, loops etc, and RStudio.
2. Linear Programming basics.
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Instructor

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How you'll learn
- Skill-based, hands-on learning - Practice new skills by completing job-related tasks. 
- Expert guidance - Follow along with pre-recorded videos from experts using a unique side-by-side interface. 
- No downloads or installation required - Access the tools and resources you need in a pre-configured cloud workspace. 
- Available only on desktop - This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices. 
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