admiral-solver 2.0.3

Python SDK for Admiral — combinatorial optimization platform

Admiral

Combinatorial optimization platform. 9 problem types, 27 proprietary algorithms, solver racing, AI advisor, and natural language formulation — all behind a single API.

Install

pip install admiral-solver

Quick Start

from admiral import Solver

solver = Solver(api_key="adm_sk_...")

# Solve a QUBO problem
result = solver.solve_qubo(Q=[[-5, 2, 4], [0, -3, 1], [0, 0, -8]])
print(result.energy)     # -13.0
print(result.solution)   # [1, 0, 1]

Problem Types

Type	Description
QUBO	Quadratic unconstrained binary optimization
Ising	Spin glass models
HUBO	Higher-order binary optimization
DQM	Discrete quadratic models
CQM	Constrained quadratic models
MAX-SAT	Maximum satisfiability
PBO	Pseudo-boolean optimization
WCSP	Weighted constraint satisfaction
Potts	Multi-state lattice models

Solver Methods

solver.solve_qubo(Q, timeout=30, num_reads=100)
solver.solve_ising(h, J, timeout=30, num_reads=100)
solver.solve_hubo(terms, num_variables, timeout=30)
solver.solve_dqm(domains, linear, quadratic, timeout=30)
solver.solve_cqm(c, Q, A, b, var_types, bounds, timeout=30)
solver.solve_maxsat(clauses, num_variables, timeout=30)
solver.solve_pbo(objective, constraints, num_variables, timeout=30)
solver.solve_wcsp(num_variables, domains, functions, timeout=30)
solver.solve_potts(num_nodes, num_states, edges, timeout=30)

Features

• Solver Racing — Race multiple solvers in parallel, return the best
• AI Advisor — Automatic solver recommendation
• NL Builder — Describe problems in English, get a formulation
• Explainability — Understand why a solution is optimal

Links

• Platform
• Dashboard
• API Docs

License

Apache 2.0