diff --git a/lib/OptimizationAccelerated/Manifest.toml b/lib/OptimizationAccelerated/Manifest.toml
index 6d2665096..128067990 100644
--- a/lib/OptimizationAccelerated/Manifest.toml
+++ b/lib/OptimizationAccelerated/Manifest.toml
@@ -905,7 +905,7 @@ version = "3.19.0"
 
 [[deps.OptimizationMOI]]
 deps = ["Ipopt_jll", "MathOptInterface", "ModelingToolkit", "Optimization", "Reexport", "SparseArrays", "Symbolics"]
-git-tree-sha1 = "0e6f35532f6b433818760ec9db5eaf623b8cba52"
+path = "../OptimizationMOI"
 uuid = "fd9f6733-72f4-499f-8506-86b2bdd0dea1"
 version = "0.1.15"
 
diff --git a/lib/OptimizationAccelerated/src/OptimizationAccelerated.jl b/lib/OptimizationAccelerated/src/OptimizationAccelerated.jl
index c183ef9c0..85a94db3d 100644
--- a/lib/OptimizationAccelerated/src/OptimizationAccelerated.jl
+++ b/lib/OptimizationAccelerated/src/OptimizationAccelerated.jl
@@ -59,13 +59,13 @@ function SciMLBase.__solve(cache::OptimizationCache{
         consjaccache .= zero(eltype(xₖ))
         cache.f.cons_j(consjaccache, xₖ)
         for j in 1:length(cache.lcons)
-            if conscache[j] < 0
+            if conscache[j] < ϵ_const
                 push!(w, -α*conscache[j] - ϵ*min(dot(consjaccache[j,:], uₖ) + α*conscache[j], 0))
                 push!(W, consjaccache[j,:])
             end
         end
-        quadprob = OptimizationProblem(OptimizationFunction((v, p =nothing) -> (v - rₖ).^2, Optimization.AutoModelingToolkit(), cons = (res, v, p = nothing) -> res .= W .* v - w), uₖ, lcons = zeros(length(w)))
-        
+        quadprob = OptimizationProblem(OptimizationFunction((v, p =nothing) -> (v .- rₖ).^2, Optimization.AutoModelingToolkit(), cons = (res, v, p = nothing) -> res .= (W .* v) .- w), uₖ, lcons = zeros(length(w)), ucons = fill(Inf, length(w)))
+
         uₖ = solve(quadprob, OSQP.Optimizer()).u
         xₖ = xₖ + Tₖ*uₖ
         if norm(uₖ, 1) < ϵ_sol
diff --git a/lib/OptimizationMOI/src/moi.jl b/lib/OptimizationMOI/src/moi.jl
index 3546637a4..d859ae6dc 100644
--- a/lib/OptimizationMOI/src/moi.jl
+++ b/lib/OptimizationMOI/src/moi.jl
@@ -13,24 +13,26 @@ struct MOIOptimizationCache{F <: OptimizationFunction, RC, LB, UB, I, S, EX,
 end
 
 function MOIOptimizationCache(prob::OptimizationProblem, opt; kwargs...)
-    isnothing(prob.f.sys) &&
+    # _f = Optimization.instantiate_function(prob.f, prob.u0, prob.f.adtype, prob.p, length(prob.ucons)) 
+    f = Optimization.instantiate_function(prob.f, prob.u0, Optimization.AutoModelingToolkit(), prob.p, length(prob.ucons))
+    isnothing(f.sys) &&
         throw(ArgumentError("Expected an `OptimizationProblem` that was setup via an `OptimizationSystem`, consider `modelingtoolkitize(prob).`"))
 
     # TODO: check if the problem is at most bilinear, i.e. affine and or quadratic terms in two variables
-    expr_map = get_expr_map(prob.f.sys)
-    expr = repl_getindex!(convert_to_expr(MTK.subs_constants(MTK.objective(prob.f.sys)),
-        prob.f.sys; expand_expr = false, expr_map))
+    expr_map = get_expr_map(f.sys)
+    expr = repl_getindex!(convert_to_expr(MTK.subs_constants(MTK.objective(f.sys)),
+        f.sys; expand_expr = false, expr_map))
 
-    cons = MTK.constraints(prob.f.sys)
+    cons = MTK.constraints(f.sys)
     cons_expr = Vector{Expr}(undef, length(cons))
     Threads.@sync for i in eachindex(cons)
         Threads.@spawn cons_expr[i] = repl_getindex!(convert_to_expr(Symbolics.canonical_form(MTK.subs_constants(cons[i])),
-            prob.f.sys;
+            f.sys;
             expand_expr = false,
             expr_map))
     end
 
-    return MOIOptimizationCache(prob.f,
+    return MOIOptimizationCache(f,
         Optimization.ReInitCache(prob.u0, prob.p),
         prob.lb,
         prob.ub,