Solving Real-World Planning Problems in Rust with SolverForge

Abstract

Scheduling, routing, allocation, and dispatch problems appear everywhere, but their real-world constraints and competing objectives can quickly overwhelm hand-written rules. In this practical talk, we will model and solve a planning problem end to end using SolverForge, an open-source planning optimization framework for Rust. We will explore how to represent the domain with ordinary Rust types, express hard constraints and softer business goals, run the solver, and inspect why one solution is better than another. The emphasis will be on building a working planning application rather than explaining the entire architecture of the library. No previous experience with optimization algorithms is required; familiarity with Rust will be helpful.

Short bio

Vittorio Distefano is the founder and lead developer of SolverForge, an open-source planning optimization framework for Rust. He is interested in decision-making software, constraint solving, and using Rust to build fast, inspectable systems for scheduling, routing, allocation, and dispatch.

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Author

Gabor Szabo (szabgab)

Gabor Szabo, the author of the Rust Maven web site maintains several Open source projects in Rust and while he still feels he has tons of new things to learn about Rust he already offers training courses in Rust and still teaches Python, Perl, git, GitHub, GitLab, CI, and testing.

Gabor Szabo