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IB DP Maths: AI SL

Revision Notes

Home / DP / Maths: AI SL / IB / Revision Notes / 3. Geometry & Trigonometry / 3.4 Voronoi Diagrams / 3.4.2 Toxic Waste Dump Problem


3.4.2 Toxic Waste Dump Problem


Toxic Waste Dump Problem

What is the toxic waste dump problem?

  • The toxic waste dump problem is the name given to the general idea of finding the point on a Voronoi diagram which is furthest from any of the sites
    • A site is the coordinates of a specific place of interest on a Voronoi diagram
  • It is given this name because of the common problem of finding a place to put a toxic waste dump that is equally far away from any inhabited area
    • For example, if a province contains five towns a Voronoi diagram could be used to find the point within the province which is furthest from each town
  • The toxic waste dump problem is more of an idea than a specific problem
    • The same concept could be applied to other contexts such as
      • Finding a position for a new supermarket that is equally far from all competitors
      • Finding a place to plant a new tree that is equally far from other trees competing for water resources
      • Finding the quietest place to enjoy a picnic that is equally far from other noisy groups of people
    • Note that the term equally far is used in all of the above examples

How is a Voronoi diagram used to find the furthest point from any site?

  • Within any Voronoi diagram the furthest point from any site will always be either
    • one of the cell vertices, or
    • somewhere on a boundary of the diagram
  • In an IB exam, the solution will always be one of the cell vertices
  • To find the furthest point you will need to consider each of the cell vertices separately and find which one is furthest from all of the sites
  • This is done by constructing the largest empty circle

What is the largest empty circle?

  • The largest empty circle is the largest possible circle constructed on a Voronoi diagram that contains no sites
  • The centre of the circle will be one of the vertices of a cell or region
    • The vertices of each region are the intersections of the boundaries
  • The radius of the circle will be the distance from the vertex to the closest site
    • The closest site will be on the circumference
    • Use Pythagoras’ Theorem to find the distance
  • There may be a scale to convert the distance found on the Voronoi diagram into a distance in real life
    • For example if the scale is 1 unit represents 5 km then 5 units represents 25 km

Worked Example

The Voronoi diagram below shows four cities at the sites A, B, C and D.  The coordinates of the points X and Y are open parentheses 5 over 4 space comma space 7 over 4 close parentheses and open parentheses 5 over 2 comma 3 over 2 close parentheses respectively.

3-4-2-diagram-for-we-2-1

Determine the optimal position where a toxic waste site could be located and, given that 1 unit represents 50 km, find the distance from this point to its nearest city.

3-4-2-toxic-waste-dump-problem-we-solution



  • 1. Number & Algebra
    • 1.1 Number Toolkit
      • 1.1.1 Standard Form
        • 1.1.2 Exponents & Logarithms
          • 1.1.3 Approximation & Estimation
            • 1.1.4 GDC: Solving Equations
            • 1.2 Sequences & Series
              • 1.2.1 Language of Sequences & Series
                • 1.2.2 Arithmetic Sequences & Series
                  • 1.2.3 Geometric Sequences & Series
                    • 1.2.4 Applications of Sequences & Series
                    • 1.3 Financial Applications
                      • 1.3.1 Compound Interest & Depreciation
                        • 1.3.2 Amortisation & Annuities
                      • 2. Functions
                        • 2.1 Linear Functions & Graphs
                          • 2.1.1 Equations of a Straight Line
                          • 2.2 Further Functions & Graphs
                            • 2.2.1 Functions
                              • 2.2.2 Graphing Functions
                                • 2.2.3 Properties of Graphs
                                • 2.3 Modelling with Functions
                                  • 2.3.1 Linear & Piecewise Models
                                    • 2.3.2 Quadratic & Cubic Models
                                      • 2.3.3 Exponential Models
                                        • 2.3.4 Direct & Inverse Variation
                                          • 2.3.5 Sinusoidal Models
                                            • 2.3.6 Strategy for Modelling Functions
                                          • 3. Geometry & Trigonometry
                                            • 3.1 Geometry Toolkit
                                              • 3.1.1 Coordinate Geometry
                                                • 3.1.2 Arcs & Sectors
                                                • 3.2 Geometry of 3D Shapes
                                                  • 3.2.1 3D Coordinate Geometry
                                                    • 3.2.2 Volume & Surface Area
                                                    • 3.3 Trigonometry
                                                      • 3.3.1 Pythagoras & Right-Angled Triganometry
                                                        • 3.3.2 Non Right-Angled Trigonometry
                                                          • 3.3.3 Applications of Trigonometry & Pythagoras
                                                          • 3.4 Voronoi Diagrams
                                                            • 3.4.1 Voronoi Diagrams
                                                              • 3.4.2 Toxic Waste Dump Problem
                                                            • 4. Statistics & Probability
                                                              • 4.1 Statistics Toolkit
                                                                • 4.1.1 Sampling & Data Collection
                                                                  • 4.1.2 Statistical Measures
                                                                    • 4.1.3 Frequency Tables
                                                                      • 4.1.4 Linear Transformations of Data
                                                                        • 4.1.5 Outliers
                                                                          • 4.1.6 Univariate Data
                                                                            • 4.1.7 Interpreting Data
                                                                            • 4.2 Correlation & Regression
                                                                              • 4.2.1 Bivariate data
                                                                                • 4.2.2 Correlation Coefficients
                                                                                  • 4.2.3 Linear Regression
                                                                                  • 4.3 Probability
                                                                                    • 4.3.1 Probability & Types of Events
                                                                                      • 4.3.2 Conditional Probability
                                                                                        • 4.3.3 Sample Space Diagrams
                                                                                        • 4.4 Probability Distributions
                                                                                          • 4.4.1 Discrete Probability Distributions
                                                                                            • 4.4.2 Expected Values
                                                                                            • 4.5 Binomial Distribution
                                                                                              • 4.5.1 The Binomial Distribution
                                                                                                • 4.5.2 Calculating Binomial Probabilities
                                                                                                • 4.6 Normal Distribution
                                                                                                  • 4.6.1 The Normal Distribution
                                                                                                    • 4.6.2 Calculations with Normal Distribution
                                                                                                    • 4.7 Hypothesis Testing
                                                                                                      • 4.7.1 Hypothesis Testing
                                                                                                        • 4.7.2 Chi-squared Test for Independence
                                                                                                          • 4.7.3 Goodness of Fit Test
                                                                                                            • 4.7.4 The t-test
                                                                                                          • 5. Calculus
                                                                                                            • 5.1 Differentiation
                                                                                                              • 5.1.1 Introduction to Differentiation
                                                                                                                • 5.1.2 Applications of Differentiation
                                                                                                                  • 5.1.3 Modelling with Differentiation
                                                                                                                  • 5.2 Integration
                                                                                                                    • 5.2.1 Trapezoid Rule: Numerical Integration
                                                                                                                      • 5.2.2 Introduction to Integration
                                                                                                                        • 5.2.3 Applications of Integration


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                                                                                                                      Author: Amber

                                                                                                                      Amber gained a first class degree in Mathematics & Meteorology from the University of Reading before training to become a teacher. She is passionate about teaching, having spent 8 years teaching GCSE and A Level Mathematics both in the UK and internationally. Amber loves creating bright and informative resources to help students reach their potential.


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