// Benchmark comparing ripopt vs ipopt on AC Optimal Power Flow (grid) problems.
//
// Run with: cargo run --release --features ipopt-native --example grid_benchmark
use ripopt::{NlpProblem, SolverOptions};
use std::time::Instant;
#[path = "../benchmarks/grid/problems.rs"]
mod problems;
// =========================================================================
// Ipopt C API FFI (same pattern as benchmark_solvers.rs)
// =========================================================================
#[cfg(feature = "ipopt-native")]
mod ipopt_ffi {
use std::ffi::CString;
use std::os::raw::c_void;
use std::time::Instant;
use ripopt::NlpProblem;
type IpoptProblemPtr = *mut c_void;
extern "C" {
fn CreateIpoptProblem(n: i32, x_l: *mut f64, x_u: *mut f64, m: i32, g_l: *mut f64, g_u: *mut f64, nele_jac: i32, nele_hess: i32, index_style: i32, eval_f: EvalFCB, eval_g: EvalGCB, eval_grad_f: EvalGradFCB, eval_jac_g: EvalJacGCB, eval_h: EvalHCB) -> IpoptProblemPtr;
fn FreeIpoptProblem(problem: IpoptProblemPtr);
fn AddIpoptStrOption(problem: IpoptProblemPtr, keyword: *const i8, val: *const i8) -> bool;
fn AddIpoptNumOption(problem: IpoptProblemPtr, keyword: *const i8, val: f64) -> bool;
fn AddIpoptIntOption(problem: IpoptProblemPtr, keyword: *const i8, val: i32) -> bool;
fn SetIntermediateCallback(problem: IpoptProblemPtr, cb: IntermediateCB) -> bool;
fn IpoptSolve(problem: IpoptProblemPtr, x: *mut f64, g: *mut f64, obj_val: *mut f64, mult_g: *mut f64, mult_x_l: *mut f64, mult_x_u: *mut f64, user_data: *mut c_void) -> i32;
}
type EvalFCB = extern "C" fn(i32, *const f64, bool, *mut f64, *mut c_void) -> bool;
type EvalGradFCB = extern "C" fn(i32, *const f64, bool, *mut f64, *mut c_void) -> bool;
type EvalGCB = extern "C" fn(i32, *const f64, bool, i32, *mut f64, *mut c_void) -> bool;
type EvalJacGCB = extern "C" fn(i32, *const f64, bool, i32, i32, *mut i32, *mut i32, *mut f64, *mut c_void) -> bool;
type EvalHCB = extern "C" fn(i32, *const f64, bool, f64, i32, *const f64, bool, i32, *mut i32, *mut i32, *mut f64, *mut c_void) -> bool;
type IntermediateCB = extern "C" fn(i32, i32, f64, f64, f64, f64, f64, f64, f64, f64, i32, *mut c_void) -> bool;
struct IpoptWrapper<'a> { problem: &'a dyn NlpProblem, jac_rows: Vec<i32>, jac_cols: Vec<i32>, hess_rows: Vec<i32>, hess_cols: Vec<i32>, iterations: i32 }
extern "C" fn eval_f_cb(n: i32, x: *const f64, _: bool, obj: *mut f64, ud: *mut c_void) -> bool { unsafe { let w = &*(ud as *const IpoptWrapper); w.problem.objective(std::slice::from_raw_parts(x, n as usize), true, &mut *obj); true } }
extern "C" fn eval_grad_f_cb(n: i32, x: *const f64, _: bool, g: *mut f64, ud: *mut c_void) -> bool { unsafe { let w = &*(ud as *const IpoptWrapper); w.problem.gradient(std::slice::from_raw_parts(x, n as usize), true, std::slice::from_raw_parts_mut(g, n as usize)); true } }
extern "C" fn eval_g_cb(n: i32, x: *const f64, _: bool, _m: i32, g: *mut f64, ud: *mut c_void) -> bool { unsafe { let w = &*(ud as *const IpoptWrapper); let m = w.problem.num_constraints(); if m > 0 { w.problem.constraints(std::slice::from_raw_parts(x, n as usize), true, std::slice::from_raw_parts_mut(g, m)); } true } }
extern "C" fn eval_jac_g_cb(n: i32, x: *const f64, _: bool, _m: i32, _nj: i32, ir: *mut i32, jc: *mut i32, vals: *mut f64, ud: *mut c_void) -> bool { unsafe { let w = &*(ud as *const IpoptWrapper); if vals.is_null() { let nele = w.jac_rows.len(); std::slice::from_raw_parts_mut(ir, nele).copy_from_slice(&w.jac_rows); std::slice::from_raw_parts_mut(jc, nele).copy_from_slice(&w.jac_cols); } else { w.problem.jacobian_values(std::slice::from_raw_parts(x, n as usize), true, std::slice::from_raw_parts_mut(vals, w.jac_rows.len())); } true } }
extern "C" fn eval_h_cb(n: i32, x: *const f64, _: bool, obj_factor: f64, _m: i32, lambda: *const f64, _: bool, _nh: i32, ir: *mut i32, jc: *mut i32, vals: *mut f64, ud: *mut c_void) -> bool { unsafe { let w = &*(ud as *const IpoptWrapper); if vals.is_null() { let nele = w.hess_rows.len(); std::slice::from_raw_parts_mut(ir, nele).copy_from_slice(&w.hess_rows); std::slice::from_raw_parts_mut(jc, nele).copy_from_slice(&w.hess_cols); } else { let xs = std::slice::from_raw_parts(x, n as usize); let m = w.problem.num_constraints(); let ls = if m > 0 { std::slice::from_raw_parts(lambda, m) } else { &[] }; w.problem.hessian_values(xs, true, obj_factor, ls, std::slice::from_raw_parts_mut(vals, w.hess_rows.len())); } true } }
extern "C" fn intermediate_cb(_: i32, iter: i32, _: f64, _: f64, _: f64, _: f64, _: f64, _: f64, _: f64, _: f64, _: i32, ud: *mut c_void) -> bool { unsafe { (*(ud as *mut IpoptWrapper)).iterations = iter; } true }
fn set_str(p: IpoptProblemPtr, k: &str, v: &str) { let ks = CString::new(k).unwrap(); let vs = CString::new(v).unwrap(); unsafe { AddIpoptStrOption(p, ks.as_ptr(), vs.as_ptr()); } }
fn set_num(p: IpoptProblemPtr, k: &str, v: f64) { let ks = CString::new(k).unwrap(); unsafe { AddIpoptNumOption(p, ks.as_ptr(), v); } }
fn set_int(p: IpoptProblemPtr, k: &str, v: i32) { let ks = CString::new(k).unwrap(); unsafe { AddIpoptIntOption(p, ks.as_ptr(), v); } }
pub fn ipopt_status_str(s: i32) -> String { match s { 0 => "Optimal".into(), 1 => "Acceptable".into(), 2 => "Infeasible".into(), -1 => "MaxIter".into(), -2 => "RestorationFailed".into(), other => format!("Status({})", other) } }
pub fn solve_ipopt(problem: &dyn NlpProblem, tol: f64, max_iter: i32) -> super::SolveResult {
let n = problem.num_variables(); let m = problem.num_constraints();
let mut x_l = vec![0.0; n]; let mut x_u = vec![0.0; n]; problem.bounds(&mut x_l, &mut x_u);
let mut g_l = vec![0.0; m.max(1)]; let mut g_u = vec![0.0; m.max(1)]; if m > 0 { problem.constraint_bounds(&mut g_l, &mut g_u); }
let (jr, jc) = problem.jacobian_structure(); let (hr, hc) = problem.hessian_structure();
let mut wrapper = IpoptWrapper { problem, jac_rows: jr.iter().map(|&r| r as i32).collect(), jac_cols: jc.iter().map(|&c| c as i32).collect(), hess_rows: hr.iter().map(|&r| r as i32).collect(), hess_cols: hc.iter().map(|&c| c as i32).collect(), iterations: 0 };
unsafe {
let ip = CreateIpoptProblem(n as i32, x_l.as_mut_ptr(), x_u.as_mut_ptr(), m as i32, g_l.as_mut_ptr(), g_u.as_mut_ptr(), wrapper.jac_rows.len() as i32, wrapper.hess_rows.len() as i32, 0, eval_f_cb, eval_g_cb, eval_grad_f_cb, eval_jac_g_cb, eval_h_cb);
set_str(ip, "sb", "yes"); set_str(ip, "mu_strategy", "adaptive"); set_num(ip, "tol", tol); set_int(ip, "max_iter", max_iter); set_int(ip, "print_level", 0);
SetIntermediateCallback(ip, intermediate_cb);
let mut x = vec![0.0; n]; problem.initial_point(&mut x);
let mut g = vec![0.0; m.max(1)]; let mut obj = 0.0; let mut mg = vec![0.0; m.max(1)]; let mut ml = vec![0.0; n]; let mut mu = vec![0.0; n];
let ud = &mut wrapper as *mut IpoptWrapper as *mut c_void;
let t0 = Instant::now();
let status = IpoptSolve(ip, x.as_mut_ptr(), g.as_mut_ptr(), &mut obj, mg.as_mut_ptr(), ml.as_mut_ptr(), mu.as_mut_ptr(), ud);
let elapsed = t0.elapsed().as_secs_f64(); let iters = wrapper.iterations; FreeIpoptProblem(ip);
super::SolveResult { status: ipopt_status_str(status), objective: obj, iterations: iters, time_s: elapsed }
}
}
}
// =========================================================================
// Result type and ripopt wrapper
// =========================================================================
struct SolveResult { status: String, objective: f64, iterations: i32, time_s: f64 }
#[derive(serde::Serialize)]
struct BenchEntry {
solver: String,
name: String,
n: usize,
m: usize,
status: String,
objective: f64,
iterations: i32,
solve_time: f64,
}
fn solve_ripopt<P: NlpProblem>(problem: &P, tol: f64, max_iter: usize) -> SolveResult {
let plvl = std::env::var("RIPOPT_PRINT_LEVEL").ok().and_then(|s| s.parse().ok()).unwrap_or(0);
let options = SolverOptions { tol, max_iter, max_wall_time: 60.0, print_level: plvl, ..SolverOptions::default() };
let t0 = Instant::now();
let result = ripopt::solve(problem, &options);
let elapsed = t0.elapsed().as_secs_f64();
SolveResult { status: format!("{:?}", result.status), objective: result.objective, iterations: result.iterations as i32, time_s: elapsed }
}
// =========================================================================
// Main
// =========================================================================
fn main() {
let tol = 1e-6;
let max_iter: usize = 3000;
let have_ipopt = cfg!(feature = "ipopt-native");
println!();
println!("AC Optimal Power Flow Benchmark: ripopt vs ipopt");
println!("================================================");
println!();
let mut header = format!(
"{:<20} {:>4} {:>4} {:>4} | {:>12} {:>5} {:>8}",
"Problem", "n", "m", "nnz", "ripopt obj", "iter", "time(s)"
);
if have_ipopt {
header += &format!(" | {:>12} {:>5} {:>8}", "ipopt obj", "iter", "time(s)");
}
println!("{}", header);
let width = header.len();
println!("{}", "-".repeat(width));
let mut results: Vec<BenchEntry> = Vec::new();
macro_rules! bench {
($name:expr, $problem:expr, $known_opt:expr) => {{
let p = $problem;
let n = p.num_variables();
let m = p.num_constraints();
let (jr, _) = p.jacobian_structure();
let nnz = jr.len();
let rp = solve_ripopt(&p, tol, max_iter);
#[allow(unused_mut)]
let mut line = format!(
"{:<20} {:>4} {:>4} {:>4} | {:>12.2} {:>5} {:>8.4}",
$name, n, m, nnz, rp.objective, rp.iterations, rp.time_s
);
#[allow(unused_mut)]
let mut notes = Vec::new();
if rp.status != "Optimal" {
notes.push(format!("ripopt={}", rp.status));
}
results.push(BenchEntry {
solver: "ripopt".into(), name: $name.into(), n, m,
status: rp.status.clone(), objective: rp.objective,
iterations: rp.iterations, solve_time: rp.time_s,
});
let rp_gap = ((rp.objective - $known_opt) / $known_opt * 100.0).abs();
#[cfg(feature = "ipopt-native")]
{
let ip = ipopt_ffi::solve_ipopt(&p, tol, max_iter as i32);
line += &format!(" | {:>12.2} {:>5} {:>8.4}", ip.objective, ip.iterations, ip.time_s);
if ip.status != "Optimal" { notes.push(format!("ipopt={}", ip.status)); }
results.push(BenchEntry {
solver: "ipopt".into(), name: $name.into(), n, m,
status: ip.status.clone(), objective: ip.objective,
iterations: ip.iterations, solve_time: ip.time_s,
});
}
println!("{}", line);
if !notes.is_empty() {
println!(" status: {}", notes.join(", "));
}
if rp_gap > 1.0 {
println!(" gap from known optimal: {:.2}%", rp_gap);
}
}};
}
use problems::*;
bench!("case3_lmbd", case3_lmbd(), 5812.64);
bench!("case5_pjm", case5_pjm(), 17551.89);
bench!("case14_ieee", case14_ieee(), 2178.08);
bench!("case30_ieee", case30_ieee(), 8081.52);
println!("{}", "-".repeat(width));
// Write JSON results
let results_path = std::env::var("RESULTS_FILE")
.unwrap_or_else(|_| "grid_results.json".to_string());
let json = serde_json::to_string_pretty(&results).unwrap();
std::fs::write(&results_path, json).unwrap();
eprintln!("Results written to {}", results_path);
}