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Linear programming

Linear programming is an optimization method that maximizes or minimizes a linear objective subject to linear equality or inequality constraints.

How 2 Manning books explain it

Statistics Every Programmer Needs

A linear program is an optimization problem with a linear objective function and linear equality or inequality constraints.

How it is used
Allocates limited resources across competing projects while maximizing priority scores under budget and strategic-balance limits.
How deep it goes
Develops variables, a linear objective, constraints, Python inputs, solver steps, and result checks; does not detail solver algorithms.
Examples
Uses a 20-feature backlog with priority scores, two budget caps, and minimum and maximum selections across three strategic groups.
What you can do after
Apply it via SciPy's linprog() to formulate and assess resource-allocation plans, checking feasibility and intended selections.

Read how Statistics Every Programmer Needs explains linear programming →

Optimization Algorithms: AI techniques for design, planning, and control problems

An optimization problem with a linear objective function and linear constraints.

How it is used
Models planning and design decisions involving linear costs, benefits, requirements, and resource mixtures.
How deep it goes
Defines linearity, works through a feed-mix formulation, and implements it in PuLP without developing solver internals.
Examples
Uses an animal feed mixture with nutrient constraints and references plant layout, wheel design, and finite catenary optimization problems.
What you can do after
Apply it via PuLP by defining variables, objectives, constraints, solving the model, and inspecting the resulting values.

Read how Optimization Algorithms: AI techniques for design, planning, and control problems explains linear programming →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.