cooptimizes

Co-optimize means to optimize two or more objectives, components, or subsystems simultaneously. In practice, it seeks solutions that balance competing criteria, often resulting in a set of optimal trade-offs rather than a single best solution. In many contexts, the process is framed as a multi-objective optimization problem, and the notion of co-optimization emphasizes joint design rather than sequential improvement. The present-tense verb form co-optimizes is commonly used in technical writing.

Applications of co-optimization appear across fields such as operations research, energy systems, computing, and logistics. In energy systems, co-optimization coordinates generation, transmission, and storage to minimize cost while meeting reliability and emission targets. In computing, it describes the joint design of hardware and software, such as compilers and processors or neural network accelerators, to achieve higher performance and energy efficiency. In logistics and supply chains, co-optimization aligns inventory, routing, and capacity planning to improve overall system efficiency.

Approaches to co-optimization include multi-objective optimization with Pareto efficiency, scalarization of objectives, and constraint programming. Co-optimization often yields a Pareto frontier, requiring decision-makers to choose a preferred point based on priorities. Computational complexity grows with the number of objectives and interdependencies among subsystems, which can necessitate approximations or specialized algorithms.

See also: Pareto efficiency, multi-objective optimization, co-design. History: the term is used across engineering and economics, reflecting a focus on joint optimization across interacting parts rather than isolated improvements.