Two Ways to Solve a Multi-Objective Problem
The weighted sum method and evolutionary algorithms both claim to solve multi-objective problems. They're doing fundamentally different things — and the difference matters for what you get out.
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Writing, tools, and open-source work at the intersection of mathematical optimization, machine learning, and applied AI.
Julian Blank, PhD
Founder, The Dual SpaceLatest Writing
View all posts »Technical writing on optimization, machine learning, and applied mathematics — aimed at practitioners.
The Pareto Front
When two objectives conflict, there is no single best solution — only trade-offs. The Pareto front is the set of solutions where you can't improve one objective without making another worse.
Domination: The Relation That Makes Multi-Objective Optimization Work
Before you can find a Pareto front, you need a way to compare solutions with multiple objectives. Domination is that comparison — and it's simpler than it sounds.