Each table: 1 h finishing. Each chair: 1 h. Available: 5 h.
Contributions: ,
Sum:
Symbol:
Inequality:
Linear Programming | Lesson 2 of 10
Pick the Symbol from the Wording
Wording
Symbol
"no more than", "at most", "available"
"at least", "minimum of"
"less than", "fewer than"
"more than", "exceeds"
Linear Programming | Lesson 2 of 10
Worked: Match Wording to Symbol
Translate, with as the left-hand side:
"No more than 30 sacks" →
"At least 5 hectares" →
"Does not exceed 100" →
"Exceeds 50,000 shillings" →
Linear Programming | Lesson 2 of 10
Quick Check: Pick the Symbol
Write the symbol; flag the strict ones:
"No more than 200 kg of maize"
"At least 5 workers on site"
"Fewer than 20 vehicles per hour"
"Available: 18 m of wire"
"Profit must exceed 100,000"
Linear Programming | Lesson 2 of 10
Predict First: "At Least 30 Sacks"
The wording: "The truck carries at least 30 sacks of maize per trip."
Let be the number of sacks. Which is correct?
A.
B.
Commit to A or B before advancing. This direction is the one most students reverse under pressure.
Linear Programming | Lesson 2 of 10
Quick Drill: Match Four Phrases
Match each phrase to its symbol:
"Reaches a minimum of 8" →
"Carries no more than 50" →
"Strictly less than 100" →
"Greater than 25, never equal" →
Linear Programming | Lesson 2 of 10
Could the Carpenter Make −3 Tables?
So far: and .
Try : ✓
And ✓
The algebra accepts negative tables.
Linear Programming | Lesson 2 of 10
The Rule the Problem Never Says
When a variable counts a physical quantity — tables, chairs, hectares, kilograms — it cannot be negative.
Write these constraints every time, even when the problem statement is silent:
The situation says it, not the wording.
Linear Programming | Lesson 2 of 10
With and Without the Non-Negativity Lines
Linear Programming | Lesson 2 of 10
A Note on Whole Numbers
In real life, the carpenter cannot make 3.7 tables.
The algebra here treats and as continuous — they may take any non-negative real value
Integrality is also implicit, but we defer it to Lesson 8
For now: continuous variables, non-negativity, and the explicit limits
Linear Programming | Lesson 2 of 10
Predict: Which Reads More Cleanly?
Two students wrote the carpenter system. Both are correct.
Student A:
Student B:
Which version makes the system easier to read and graph in Lesson 3?
Linear Programming | Lesson 2 of 10
Template for a Complete System
One line per inequality
— first
Non-negativity last
Objective separate
Linear Programming | Lesson 2 of 10
The Full Carpenter System on Paper
Constraints:
Objective (set up only):
Linear Programming | Lesson 2 of 10
Predict: Does Profit Belong Here?
A student writes:
Does the last line belong with the others?
If not, where does go?
Linear Programming | Lesson 2 of 10
Constraint vs. Objective: the Difference
Constraint
Objective
RHS
Fixed number
None
Direction
max or min
Example
Linear Programming | Lesson 2 of 10
Validate the System with
Pick a plan that should be feasible — substitute into every constraint:
✓
✓
✓ and ✓
Linear Programming | Lesson 2 of 10
Your Turn: The Tailor Problem
Shirts (), trousers (). Shirt: 2 m cloth, 1 h sewing. Trouser: 3 m, 2 h. Have 24 m, 14 h.
In pairs, produce: definitions, both constraints, non-negativity, validation, objective.
Linear Programming | Lesson 2 of 10
Exit Task: The Baker, On Your Own
Loaves (), cakes (). Loaf: 0.5 kg flour, 10 min. Cake: 0.3 kg, 20 min. Have 5 kg, 240 min. Profit: 2,000 UGX/loaf, 5,000/cake.
Produce the complete setup — no scaffolding. 3 minutes.
Linear Programming | Lesson 2 of 10
Four Mistakes to Catch and Fix
M1. Missing non-negativity → always write M2. Flipped symbol → "at least" ; read aloud M3. Mixed vs → always M4. Profit as constraint → objective has no RHS number
Linear Programming | Lesson 2 of 10
Today's System Is Tomorrow's Graph
A worded LP problem becomes:
✓ A system of inequalities — with non-negativity
✓ A separate objective to maximise or minimise