move to get_sort as method, add opt_lns pass, disable xor simplification unless configured, fix perf bug in model converter update trail

src/opt/opt_lns.h

@@ -0,0 +1,52 @@
+/*++
+Copyright (c) 2014 Microsoft Corporation
+
+Module Name:
+
+    opt_lns.h
+
+Abstract:
+   
+    "large" neighborhood search for maxsat problem instances.
+
+    Start with a model that we assume satisfies at least one of the soft constraint assumptions.
+    Attempt to improve the model locally by invoking the SAT solver with a phase
+    fixed to be the assignment that solved the previous instance.
+    Local improvement is performed by hardening each soft constraint in turn.
+    The soft constraints are assumed sorted by weight, such that the highest 
+    weight soft constraint is first, followed by soft constraints of lower weight.
+
+Author:
+
+    Nikolaj Bjorner (nbjorner) 2021-02-01
+
+--*/
+
+#pragma once
+
+namespace opt {
+
+    class lns {
+        ast_manager&     m;
+        solver&          s;
+        expr_ref_vector  m_hardened;
+        expr_ref_vector  m_soft;
+        unsigned         m_max_conflicts { 1000 };
+        unsigned         m_num_improves { 0 };
+        std::function<void(model_ref& m)> m_update_model;
+
+        expr* soft(unsigned i) const { return m_soft[i]; }
+        void  set_lns_params();
+        void  save_defaults(params_ref& p);
+        unsigned improve_step(model_ref& mdl);
+        lbool improve_step(model_ref& mdl, expr* e);
+        unsigned improve_linear(model_ref& mdl);
+        unsigned improve_rotate(model_ref& mdl, expr_ref_vector const& asms);
+        void  setup_assumptions(model_ref& mdl, expr_ref_vector const& asms);
+
+    public:
+        lns(solver& s, std::function<void(model_ref&)>& update_model);
+        void set_conflicts(unsigned c) { m_max_conflicts = c; }
+        unsigned climb(model_ref& mdl, expr_ref_vector const& asms);
+    };
+};