Building an Affordable LP Solver API for $5/month
The article discusses the high cost and licensing challenges of commercial LP/MIP solvers like Gurobi and CPLEX, leading the author to build their own affordable API solution using the open-source HiGHS solver.
Why it matters
This news highlights the accessibility challenges of commercial optimization solvers and the opportunity for open-source alternatives to provide more affordable and flexible solutions for developers.
Key Points
- 1Commercial LP/MIP solvers like Gurobi and CPLEX are prohibitively expensive for most developers, with annual costs of $10,000 to $50,000
- 2The licensing models of these commercial solvers are also incompatible with modern cloud-based infrastructure and autoscaling
- 3The author built an API solution using the open-source HiGHS solver, offering a more affordable and accessible alternative at $5/month
- 4While commercial solvers excel at large-scale industrial problems, open-source options like HiGHS can suffice for most developers' needs with minimal performance impact
Details
The article discusses the high cost and licensing challenges of commercial linear programming (LP) and mixed-integer programming (MIP) solvers, which are designed for large enterprises and not accessible to most developers. The author found that Gurobi, the industry-leading solver, costs $10,000 to $50,000 per year, with a licensing model that is incompatible with modern cloud-based infrastructure. Frustrated by the lack of transparent pricing and self-service options, the author decided to build their own API solution using the open-source HiGHS solver, which is proven in production and offers a more affordable and accessible alternative at just $5 per month. While commercial solvers like Gurobi and CPLEX excel at solving large-scale industrial problems with millions of variables, the author argues that for most developers' needs, the performance gap between these expensive tools and open-source options is negligible, measured in microseconds rather than hours.
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