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DP IB Maths: AI SL

Revision Notes

Home / IB / Maths: AI SL / DP / 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

Exam Tip

  • The solution to the toxic waste dump will always be one of the points of intersection between the perpendicular bisectors, so you need to know the coordinates of these points
    • Remember that you can use your GDC to solve a pair of the simultaneous equations quickly if you know the equations of two of the perpendicular bisectors that intersect at that point

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
                                                                                                                      Amber Perry

                                                                                                                      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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