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Task 1 (MILP Model + R Implementation) This Section Must Include: Problem Explanation Briefly explain the GI endoscopy capacity planning problem. Identify the goal: minimize total cost while meeting weekly diagnostic

ITAO7104 Data-Driven Decision-Making

ITAO7104 Assignment Brief 

Instructions

The report must contain two sections only: Section A (Task 1) and Section B (Task 2) in the same report file.

General Requirements

– MSc Business Analytics

  • Module: Data-Driven Decision-Making (D3M – ITAO7104) Report must contain ONLY TWO SECTIONS:

○ Section A – Task 1

○ Section B – Task 2

  • NO appendix allowed in the report.
  • Use 12pt font for body text and 14pt bold for section headings.
  • Leave the cover page for me.
  • Include page numbers at bottom of pages.
  • Word count must be within ±10% of the limit.
  • Overall Turnitin similarity must stay below 25%.
  • Follow the rubric/marking criteria carefully for scoring.
  • Write clearly and professionally with logical explanations and structure.
  • Use Harvard referencing style for all citations.
  • Visualizations and screenshots must be clear and readable (not too big or too small).

SECTION A – Task 1 (MILP Model + R Implementation) This section must include:

  1. Problem Explanation
    • Briefly explain the GI endoscopy capacity planning problem.
    • Identify the goal: minimize total cost while meeting weekly diagnostic and therapeutic demand.
  2. Mathematical Model (MILP) Clearly define:

Indices

  • Rooms (r) Weeks (w)

Parameters

  • Diagnostic demand per week
  • Therapeutic demand per week
  • Clinician hours available
  • Room capacities
  • Setup costs Allocation costs

Decision Variables

  • Whether room r is:
    • unavailable

○ diagnostic configuration ○ therapeutic configuration Constraints Include:

  • Demand satisfaction for diagnostic procedures
  • Demand satisfaction for therapeutic procedures
  • Room capacity limits
  • Clinician hour limits
  • Only one configuration per room per week
  • Therapeutic procedures only allowed in therapeutic rooms

Objective Function

  • Minimize total cost (setup + allocation cost).

Explain why each constraint exists and which part of the problem it represents.

Hii

  1. Solve using R
    • Use R with the ompr package and a solver (GLPK / HiGHS / Symphony etc.).
    • Include screenshots of R code and solver output in the report.
    • Code must have short comments explaining key steps.

Also submit the functional R code file separately.

  1. Results Explanation

Explain in plain English:

  • Which rooms are used each week
  • Which configuration each room has
  • How diagnostic and therapeutic hours are allocated State clearly:
  • Minimum total cost
  • MILP optimality gap
  1. Visualizations

Include charts such as:

Chart 1 ● Stacked chart showing each room’s configuration over the 26 weeks.

Chart 2

  • Weekly aggregated capacity showing:
    • diagnostic hours

○ therapeutic hours

Charts must be clear and properly labeled.

Section B – Task 2 (Essay – max 1250 words)

Choose one healthcare journal article from the QUB library that uses MILP with an exact solution method.

Structure the essay using these headings:

  1. Healthcare Problem
    • Explain the healthcare operational problem.
    • Why it matters in practice.
  2. MILP Model Outline

Explain in simple terms:

  • Decision variables
  • Constraints
  • Objective

Use bullet points instead of equations.

  1. Exact Method Used

Explain the optimization method used in the article (for example branch-and-bound, branchand-price, etc.).

Describe how the method works in the study.

  1. Method–Problem Fit

Explain why the chosen method works well for the model.

Discuss aspects like:

  • scalability
  • structure of the MILP
  • computational efficiency
  1. Limitations and Practical InsightDiscuss:
  • limitations of the model
  • real-world challenges
  • implementation issues in healthcare

Additional requirements

  • Use Harvard references.
  • The main article must be bold in the bibliography.
  • The article must be recent if possible (preferably after 2023).
  • You may include up to 5 additional references.
  • Include at least one figure from the article with caption and citation.
  • Provide the journal hyperlink in the reference list.

Final Deliverables

1. Assignment Report (Word or PDF) Contains:

  • Section A
  • Section B

2. R Code File (.R): Must run without errors and produce the same results shown in the report.

3. All screenshots must be clear and readable.

Please ensure the work is clear, well-structured, and written professionally according to the rubric.

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