LEARN · EXPLAIN · REVISE

Does the displayed objective have a maximum over x,y≥0?

Read the idea, work independently, then explain what changed.

T04高二理組數學思維本(2026).pdf · III. Simple linear programming · PDF 11 / printed page 10

TOPIC 01

Linear programming and discrete feasibility

Draw a feasible region and optimise a linear objective, then check integer restrictions when required.

Draw a feasible region and optimise a linear objective, then check integer restrictions when required.
Justify the method and check the conditions in a new situation.

Use one hint at a time. A correction explains what changed, not just the final answer.

01 / Standard#Worked example

z=3x+y

A vertex search needs a nonempty bounded polygon or a justified finite optimum; integer solutions may differ from continuous optima.

Skills and prerequisite lessons

Working and explanation

BUILD THE REASONING

Hint 1

Write the defining equation, retain exclusions, and then solve or compare.

Hint 2

Try the feasible ray (x,y)=(s,0).

Worked solution

The requested relation or conclusion is shown below.

\text{unbounded above}

Checks and common pitfalls: No resource constraint blocks growth along the feasible ray.

Reasoning checklist · self / teacher assessment

Think first. Reveal a hint when the class is ready.

Teacher preparation and assessment

Draw a feasible region and optimise a linear objective, then check integer restrictions when required.
Which condition is essential in linear programming and discrete feasibility?
Must rounding a continuous optimum preserve feasibility?

Model or definition: Draw a feasible region and optimise a linear objective, then check integer restrictions when required.
$z=ax+by$
Conditions: A vertex search needs a nonempty bounded polygon or a justified finite optimum; integer solutions may differ from continuous optima.

An objective has no optimum if it is unbounded in an improving feasible direction.