<ahref="parameters_8h.html">Go to the documentation of this file.</a><divclass="fragment"><divclass="line"><aid="l00001"name="l00001"></a><spanclass="lineno"> 1</span><spanclass="comment">// Copyright 2010-2021 Google LLC</span></div>
<divclass="line"><aid="l00002"name="l00002"></a><spanclass="lineno"> 2</span><spanclass="comment">// Licensed under the Apache License, Version 2.0 (the "License");</span></div>
<divclass="line"><aid="l00003"name="l00003"></a><spanclass="lineno"> 3</span><spanclass="comment">// you may not use this file except in compliance with the License.</span></div>
<divclass="line"><aid="l00004"name="l00004"></a><spanclass="lineno"> 4</span><spanclass="comment">// You may obtain a copy of the License at</span></div>
<divclass="line"><aid="l00008"name="l00008"></a><spanclass="lineno"> 8</span><spanclass="comment">// Unless required by applicable law or agreed to in writing, software</span></div>
<divclass="line"><aid="l00009"name="l00009"></a><spanclass="lineno"> 9</span><spanclass="comment">// distributed under the License is distributed on an "AS IS" BASIS,</span></div>
<divclass="line"><aid="l00010"name="l00010"></a><spanclass="lineno"> 10</span><spanclass="comment">// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span></div>
<divclass="line"><aid="l00011"name="l00011"></a><spanclass="lineno"> 11</span><spanclass="comment">// See the License for the specific language governing permissions and</span></div>
<divclass="line"><aid="l00012"name="l00012"></a><spanclass="lineno"> 12</span><spanclass="comment">// limitations under the License.</span></div>
<divclass="line"><aid="l00040"name="l00040"></a><spanclass="lineno"> 40</span><spanclass="comment">// It supports both MIPs and LPs. No dual data for LPs is returned though. To</span></div>
<divclass="line"><aid="l00041"name="l00041"></a><spanclass="lineno"> 41</span><spanclass="comment">// solve LPs, kGlop should be preferred.</span></div>
<divclass="line"><aid="l00056"name="l00056"></a><spanclass="lineno"> 56</span><spanclass="comment">// It supports solving IPs and can scale MIPs to solve them as IPs.</span></div>
<divclass="line"><aid="l00063"name="l00063"></a><spanclass="lineno"> 63</span><spanclass="comment">// Thread-safety: GLPK use thread-local storage for memory allocations. As a</span></div>
<divclass="line"><aid="l00064"name="l00064"></a><spanclass="lineno"> 64</span><spanclass="comment">// consequence when using IncrementalSolver, the user must make sure that</span></div>
<divclass="line"><aid="l00065"name="l00065"></a><spanclass="lineno"> 65</span><spanclass="comment">// instances are destroyed on the same thread as they are created or GLPK will</span></div>
<divclass="line"><aid="l00066"name="l00066"></a><spanclass="lineno"> 66</span><spanclass="comment">// crash. It seems OK to call IncrementalSolver::Solve() from another thread</span></div>
<divclass="line"><aid="l00067"name="l00067"></a><spanclass="lineno"> 67</span><spanclass="comment">// than the one used to create the Solver but it is not documented by GLPK and</span></div>
<divclass="line"><aid="l00068"name="l00068"></a><spanclass="lineno"> 68</span><spanclass="comment">// should be avoided. Of course these limitations do not apply to the Solve()</span></div>
<divclass="line"><aid="l00069"name="l00069"></a><spanclass="lineno"> 69</span><spanclass="comment">// function that recreates a new GLPK problem in the calling thread and</span></div>
<divclass="line"><aid="l00070"name="l00070"></a><spanclass="lineno"> 70</span><spanclass="comment">// destroys before returning.</span></div>
<divclass="line"><aid="l00072"name="l00072"></a><spanclass="lineno"> 72</span><spanclass="comment">// When solving a LP with the presolver, a solution (and the unbound rays) are</span></div>
<divclass="line"><aid="l00073"name="l00073"></a><spanclass="lineno"> 73</span><spanclass="comment">// only returned if an optimal solution has been found. Else nothing is</span></div>
<divclass="line"><aid="l00074"name="l00074"></a><spanclass="lineno"> 74</span><spanclass="comment">// returned. See glpk-5.0/doc/glpk.pdf page #40 available from glpk-5.0.tar.gz</span></div>
<divclass="line"><aid="l00075"name="l00075"></a><spanclass="lineno"> 75</span><spanclass="comment">// for details.</span></div>
<divclass="line"><aid="l00084"name="l00084"></a><spanclass="lineno"> 84</span><spanclass="comment">// The expected values are the one returned by EnumToString().</span></div>
<divclass="line"><aid="l00090"name="l00090"></a><spanclass="lineno"> 90</span><spanclass="comment">// The returned values are the same as EnumToString().</span></div>
<divclass="line"><aid="l00093"name="l00093"></a><spanclass="lineno"> 93</span><spanclass="comment">// Selects an algorithm for solving linear programs.</span></div>
<divclass="line"><aid="l00095"name="l00095"></a><spanclass="lineno"> 95</span><spanclass="comment">// The (primal) simplex method. Typically can provide primal and dual</span></div>
<divclass="line"><aid="l00096"name="l00096"></a><spanclass="lineno"> 96</span><spanclass="comment">// solutions, primal/dual rays on primal/dual unbounded problems, and a basis.</span></div>
<divclass="line"><aid="l00099"name="l00099"></a><spanclass="lineno"> 99</span><spanclass="comment">// The dual simplex method. Typically can provide primal and dual</span></div>
<divclass="line"><aid="l00100"name="l00100"></a><spanclass="lineno"> 100</span><spanclass="comment">// solutions, primal/dual rays on primal/dual unbounded problems, and a basis.</span></div>
<divclass="line"><aid="l00103"name="l00103"></a><spanclass="lineno"> 103</span><spanclass="comment">// The barrier method, also commonly called an interior point method (IPM).</span></div>
<divclass="line"><aid="l00104"name="l00104"></a><spanclass="lineno"> 104</span><spanclass="comment">// Can typically give both primal and dual solutions. Some implementations can</span></div>
<divclass="line"><aid="l00105"name="l00105"></a><spanclass="lineno"> 105</span><spanclass="comment">// also produce rays on unbounded/infeasible problems. A basis is not given</span></div>
<divclass="line"><aid="l00106"name="l00106"></a><spanclass="lineno"> 106</span><spanclass="comment">// unless the underlying solver does "crossover" and finishes with simplex.</span></div>
<divclass="line"><aid="l00112"name="l00112"></a><spanclass="lineno"> 112</span><spanclass="comment">// Effort level applied to an optional task while solving (see SolveParameters</span></div>
<divclass="line"><aid="l00113"name="l00113"></a><spanclass="lineno"> 113</span><spanclass="comment">// for use).</span></div>
<divclass="line"><aid="l00115"name="l00115"></a><spanclass="lineno"> 115</span><spanclass="comment">// Typically used as a std::optional<Emphasis>. It used to configure a solver</span></div>
<divclass="line"><aid="l00116"name="l00116"></a><spanclass="lineno"> 116</span><spanclass="comment">// feature as follows:</span></div>
<divclass="line"><aid="l00117"name="l00117"></a><spanclass="lineno"> 117</span><spanclass="comment">// * If a solver doesn't support the feature, only nullopt will always be</span></div>
<divclass="line"><aid="l00118"name="l00118"></a><spanclass="lineno"> 118</span><spanclass="comment">// valid, any other setting will give an invalid argument error (some solvers</span></div>
<divclass="line"><aid="l00119"name="l00119"></a><spanclass="lineno"> 119</span><spanclass="comment">// may also accept kOff).</span></div>
<divclass="line"><aid="l00120"name="l00120"></a><spanclass="lineno"> 120</span><spanclass="comment">// * If the solver supports the feature:</span></div>
<divclass="line"><aid="l00121"name="l00121"></a><spanclass="lineno"> 121</span><spanclass="comment">// - When unset, the underlying default is used.</span></div>
<divclass="line"><aid="l00122"name="l00122"></a><spanclass="lineno"> 122</span><spanclass="comment">// - When the feature cannot be turned off, kOff will return an error.</span></div>
<divclass="line"><aid="l00123"name="l00123"></a><spanclass="lineno"> 123</span><spanclass="comment">// - If the feature is enabled by default, the solver default is typically</span></div>
<divclass="line"><aid="l00124"name="l00124"></a><spanclass="lineno"> 124</span><spanclass="comment">// mapped to kMedium.</span></div>
<divclass="line"><aid="l00125"name="l00125"></a><spanclass="lineno"> 125</span><spanclass="comment">// - If the feature is supported, kLow, kMedium, kHigh, and kVeryHigh will</span></div>
<divclass="line"><aid="l00126"name="l00126"></a><spanclass="lineno"> 126</span><spanclass="comment">// never give an error, and will map onto their best match.</span></div>
<divclass="line"><aid="l00137"name="l00137"></a><spanclass="lineno"> 137</span><spanclass="comment">// Gurobi specific parameters for solving. See</span></div>
<divclass="line"><aid="l00145"name="l00145"></a><spanclass="lineno"> 145</span><spanclass="comment">// With Gurobi, the order that parameters are applied can have an impact in rare</span></div>
<divclass="line"><aid="l00146"name="l00146"></a><spanclass="lineno"> 146</span><spanclass="comment">// situations. Parameters are applied in the following order:</span></div>
<divclass="line"><aid="l00147"name="l00147"></a><spanclass="lineno"> 147</span><spanclass="comment">// * LogToConsole is set from SolveParameters.enable_output.</span></div>
<divclass="line"><aid="l00148"name="l00148"></a><spanclass="lineno"> 148</span><spanclass="comment">// * Any common parameters not overwritten by GurobiParameters.</span></div>
<divclass="line"><aid="l00149"name="l00149"></a><spanclass="lineno"> 149</span><spanclass="comment">// * param_values in iteration order (insertion order).</span></div>
<divclass="line"><aid="l00150"name="l00150"></a><spanclass="lineno"> 150</span><spanclass="comment">// We set LogToConsole first because setting other parameters can generate</span></div>
<divclass="line"><aid="l00153"name="l00153"></a><spanclass="lineno"> 153</span><spanclass="comment">// Parameter name-value pairs to set in insertion order.</span></div>
<divclass="line"><aid="l00162"name="l00162"></a><spanclass="lineno"> 162</span><spanclass="comment">// Parameters to control a single solve.</span></div>
<divclass="line"><aid="l00164"name="l00164"></a><spanclass="lineno"> 164</span><spanclass="comment">// Contains both parameters common to all solvers e.g. time_limit, and</span></div>
<divclass="line"><aid="l00165"name="l00165"></a><spanclass="lineno"> 165</span><spanclass="comment">// parameters for a specific solver, e.g. gscip. If a value is set in both</span></div>
<divclass="line"><aid="l00166"name="l00166"></a><spanclass="lineno"> 166</span><spanclass="comment">// common and solver specific field, the solver specific setting is used.</span></div>
<divclass="line"><aid="l00168"name="l00168"></a><spanclass="lineno"> 168</span><spanclass="comment">// The common parameters that are optional and unset indicate that the solver</span></div>
<divclass="line"><aid="l00169"name="l00169"></a><spanclass="lineno"> 169</span><spanclass="comment">// default is used.</span></div>
<divclass="line"><aid="l00171"name="l00171"></a><spanclass="lineno"> 171</span><spanclass="comment">// Solver specific parameters for solvers other than the one in use are ignored.</span></div>
<divclass="line"><aid="l00173"name="l00173"></a><spanclass="lineno"> 173</span><spanclass="comment">// Parameters that depends on the model (e.g. branching priority is set for</span></div>
<divclass="line"><aid="l00174"name="l00174"></a><spanclass="lineno"> 174</span><spanclass="comment">// each variable) are passed in ModelSolveParametersProto.</span></div>
<divclass="line"><aid="l00176"name="l00176"></a><spanclass="lineno"> 176</span><spanclass="comment">// Enables printing the solver implementation traces. These traces are sent</span></div>
<divclass="line"><aid="l00177"name="l00177"></a><spanclass="lineno"> 177</span><spanclass="comment">// to the standard output stream.</span></div>
<divclass="line"><aid="l00179"name="l00179"></a><spanclass="lineno"> 179</span><spanclass="comment">// Note that if the solver supports message callback and the user registers a</span></div>
<divclass="line"><aid="l00180"name="l00180"></a><spanclass="lineno"> 180</span><spanclass="comment">// callback for it, then this parameter value is ignored and no traces are</span></div>
<divclass="line"><aid="l00184"name="l00184"></a><spanclass="lineno"> 184</span><spanclass="comment">// Maximum time a solver should spend on the problem.</span></div>
<divclass="line"><aid="l00186"name="l00186"></a><spanclass="lineno"> 186</span><spanclass="comment">// This value is not a hard limit, solve time may slightly exceed this value.</span></div>
<divclass="line"><aid="l00187"name="l00187"></a><spanclass="lineno"> 187</span><spanclass="comment">// Always passed to the underlying solver, the solver default is not used.</span></div>
<divclass="line"><aid="l00190"name="l00190"></a><spanclass="lineno"> 190</span><spanclass="comment">// Limit on the iterations of the underlying algorithm (e.g. simplex pivots).</span></div>
<divclass="line"><aid="l00191"name="l00191"></a><spanclass="lineno"> 191</span><spanclass="comment">// The specific behavior is dependent on the solver and algorithm used, but</span></div>
<divclass="line"><aid="l00192"name="l00192"></a><spanclass="lineno"> 192</span><spanclass="comment">// often can give a deterministic solve limit (further configuration may be</span></div>
<divclass="line"><aid="l00193"name="l00193"></a><spanclass="lineno"> 193</span><spanclass="comment">// needed, e.g. one thread).</span></div>
<divclass="line"><aid="l00195"name="l00195"></a><spanclass="lineno"> 195</span><spanclass="comment">// Typically supported by LP, QP, and MIP solvers, but for MIP solvers see</span></div>
<divclass="line"><aid="l00196"name="l00196"></a><spanclass="lineno"> 196</span><spanclass="comment">// also node_limit.</span></div>
<divclass="line"><aid="l00199"name="l00199"></a><spanclass="lineno"> 199</span><spanclass="comment">// Limit on the number of subproblems solved in enumerative search (e.g.</span></div>
<divclass="line"><aid="l00200"name="l00200"></a><spanclass="lineno"> 200</span><spanclass="comment">// branch and bound). For many solvers this can be used to deterministically</span></div>
<divclass="line"><aid="l00201"name="l00201"></a><spanclass="lineno"> 201</span><spanclass="comment">// limit computation (further configuration may be needed, e.g. one thread).</span></div>
<divclass="line"><aid="l00203"name="l00203"></a><spanclass="lineno"> 203</span><spanclass="comment">// Typically for MIP solvers, see also iteration_limit.</span></div>
<divclass="line"><aid="l00206"name="l00206"></a><spanclass="lineno"> 206</span><spanclass="comment">// The solver stops early if it can prove there are no primal solutions at</span></div>
<divclass="line"><aid="l00207"name="l00207"></a><spanclass="lineno"> 207</span><spanclass="comment">// least as good as cutoff.</span></div>
<divclass="line"><aid="l00209"name="l00209"></a><spanclass="lineno"> 209</span><spanclass="comment">// On an early stop, the solver returns termination reason kNoSolutionFound</span></div>
<divclass="line"><aid="l00210"name="l00210"></a><spanclass="lineno"> 210</span><spanclass="comment">// and with limit kCutoff and is not required to give any extra solution</span></div>
<divclass="line"><aid="l00211"name="l00211"></a><spanclass="lineno"> 211</span><spanclass="comment">// information. Has no effect on the return value if there is no early stop.</span></div>
<divclass="line"><aid="l00213"name="l00213"></a><spanclass="lineno"> 213</span><spanclass="comment">// It is recommended that you use a tolerance if you want solutions with</span></div>
<divclass="line"><aid="l00214"name="l00214"></a><spanclass="lineno"> 214</span><spanclass="comment">// objective exactly equal to cutoff to be returned.</span></div>
<divclass="line"><aid="l00216"name="l00216"></a><spanclass="lineno"> 216</span><spanclass="comment">// See the user guide for more details and a comparison with best_bound_limit.</span></div>
<divclass="line"><aid="l00219"name="l00219"></a><spanclass="lineno"> 219</span><spanclass="comment">// The solver stops early as soon as it finds a solution at least this good,</span></div>
<divclass="line"><aid="l00220"name="l00220"></a><spanclass="lineno"> 220</span><spanclass="comment">// with termination reason kFeasible and limit kObjective.</span></div>
<divclass="line"><aid="l00223"name="l00223"></a><spanclass="lineno"> 223</span><spanclass="comment">// The solver stops early as soon as it proves the best bound is at least this</span></div>
<divclass="line"><aid="l00224"name="l00224"></a><spanclass="lineno"> 224</span><spanclass="comment">// good, with termination reason kFeasible or kNoSolutionFound and limit</span></div>
<divclass="line"><aid="l00227"name="l00227"></a><spanclass="lineno"> 227</span><spanclass="comment">// See the user guide for a comparison with cutoff_limit.</span></div>
<divclass="line"><aid="l00230"name="l00230"></a><spanclass="lineno"> 230</span><spanclass="comment">// The solver stops early after finding this many feasible solutions, with</span></div>
<divclass="line"><aid="l00231"name="l00231"></a><spanclass="lineno"> 231</span><spanclass="comment">// termination reason kFeasible and limit kSolution. Must be greater than</span></div>
<divclass="line"><aid="l00232"name="l00232"></a><spanclass="lineno"> 232</span><spanclass="comment">// zero if set. It is often used get the solver to stop on the first feasible</span></div>
<divclass="line"><aid="l00233"name="l00233"></a><spanclass="lineno"> 233</span><spanclass="comment">// solution found. Note that there is no guarantee on the objective value for</span></div>
<divclass="line"><aid="l00234"name="l00234"></a><spanclass="lineno"> 234</span><spanclass="comment">// any of the returned solutions.</span></div>
<divclass="line"><aid="l00236"name="l00236"></a><spanclass="lineno"> 236</span><spanclass="comment">// Solvers will typically not return more solutions than the solution limit,</span></div>
<divclass="line"><aid="l00237"name="l00237"></a><spanclass="lineno"> 237</span><spanclass="comment">// but this is not enforced by MathOpt, see also b/214041169.</span></div>
<divclass="line"><aid="l00239"name="l00239"></a><spanclass="lineno"> 239</span><spanclass="comment">// Currently supported for Gurobi and SCIP, and for CP-SAT only with value 1.</span></div>
<divclass="line"><aid="l00242"name="l00242"></a><spanclass="lineno"> 242</span><spanclass="comment">// If unset, use the solver default. If set, it must be >= 1.</span></div>
<divclass="line"><aid="l00245"name="l00245"></a><spanclass="lineno"> 245</span><spanclass="comment">// Seed for the pseudo-random number generator in the underlying</span></div>
<divclass="line"><aid="l00246"name="l00246"></a><spanclass="lineno"> 246</span><spanclass="comment">// solver. Note that all solvers use pseudo-random numbers to select things</span></div>
<divclass="line"><aid="l00247"name="l00247"></a><spanclass="lineno"> 247</span><spanclass="comment">// such as perturbation in the LP algorithm, for tie-break-up rules, and for</span></div>
<divclass="line"><aid="l00248"name="l00248"></a><spanclass="lineno"> 248</span><spanclass="comment">// heuristic fixings. Varying this can have a noticeable impact on solver</span></div>
<divclass="line"><aid="l00251"name="l00251"></a><spanclass="lineno"> 251</span><spanclass="comment">// Although all solvers have a concept of seeds, note that valid values</span></div>
<divclass="line"><aid="l00252"name="l00252"></a><spanclass="lineno"> 252</span><spanclass="comment">// depend on the actual solver.</span></div>
<divclass="line"><aid="l00253"name="l00253"></a><spanclass="lineno"> 253</span><spanclass="comment">// - Gurobi: [0:GRB_MAXINT] (which as of Gurobi 9.0 is 2x10^9).</span></div>
<divclass="line"><aid="l00254"name="l00254"></a><spanclass="lineno"> 254</span><spanclass="comment">// - GSCIP: [0:2147483647] (which is MAX_INT or kint32max or 2^31-1).</span></div>
<divclass="line"><aid="l00255"name="l00255"></a><spanclass="lineno"> 255</span><spanclass="comment">// - GLOP: [0:2147483647] (same as above)</span></div>
<divclass="line"><aid="l00256"name="l00256"></a><spanclass="lineno"> 256</span><spanclass="comment">// In all cases, the solver will receive a value equal to:</span></div>
<divclass="line"><aid="l00260"name="l00260"></a><spanclass="lineno"> 260</span><spanclass="comment">// An absolute optimality tolerance (primarily) for MIP solvers.</span></div>
<divclass="line"><aid="l00262"name="l00262"></a><spanclass="lineno"> 262</span><spanclass="comment">// The absolute GAP is the absolute value of the difference between:</span></div>
<divclass="line"><aid="l00263"name="l00263"></a><spanclass="lineno"> 263</span><spanclass="comment">// * the objective value of the best feasible solution found,</span></div>
<divclass="line"><aid="l00264"name="l00264"></a><spanclass="lineno"> 264</span><spanclass="comment">// * the dual bound produced by the search.</span></div>
<divclass="line"><aid="l00265"name="l00265"></a><spanclass="lineno"> 265</span><spanclass="comment">// The solver can stop once the absolute GAP is at most absolute_gap_tolerance</span></div>
<divclass="line"><aid="l00266"name="l00266"></a><spanclass="lineno"> 266</span><spanclass="comment">// (when set), and return TerminationReason::kOptimal.</span></div>
<divclass="line"><aid="l00273"name="l00273"></a><spanclass="lineno"> 273</span><spanclass="comment">// A relative optimality tolerance (primarily) for MIP solvers.</span></div>
<divclass="line"><aid="l00275"name="l00275"></a><spanclass="lineno"> 275</span><spanclass="comment">// The relative GAP is a normalized version of the absolute GAP (defined on</span></div>
<divclass="line"><aid="l00276"name="l00276"></a><spanclass="lineno"> 276</span><spanclass="comment">// absolute_gap_tolerance), where the normalization is solver-dependent, e.g.</span></div>
<divclass="line"><aid="l00277"name="l00277"></a><spanclass="lineno"> 277</span><spanclass="comment">// the absolute GAP divided by the objective value of the best feasible</span></div>
<divclass="line"><aid="l00280"name="l00280"></a><spanclass="lineno"> 280</span><spanclass="comment">// The solver can stop once the relative GAP is at most relative_gap_tolerance</span></div>
<divclass="line"><aid="l00281"name="l00281"></a><spanclass="lineno"> 281</span><spanclass="comment">// (when set), and return TerminationReason::kOptimal.</span></div>
<divclass="line"><aid="l00288"name="l00288"></a><spanclass="lineno"> 288</span><spanclass="comment">// The algorithm for solving a linear program. If nullopt, use the solver</span></div>
<divclass="line"><aid="l00291"name="l00291"></a><spanclass="lineno"> 291</span><spanclass="comment">// For problems that are not linear programs but where linear programming is</span></div>
<divclass="line"><aid="l00292"name="l00292"></a><spanclass="lineno"> 292</span><spanclass="comment">// a subroutine, solvers may use this value. E.g. MIP solvers will typically</span></div>
<divclass="line"><aid="l00293"name="l00293"></a><spanclass="lineno"> 293</span><spanclass="comment">// use this for the root LP solve only (and use dual simplex otherwise).</span></div>
<divclass="line"><aid="l00296"name="l00296"></a><spanclass="lineno"> 296</span><spanclass="comment">// Effort on simplifying the problem before starting the main algorithm, or</span></div>
<divclass="line"><aid="l00297"name="l00297"></a><spanclass="lineno"> 297</span><spanclass="comment">// the solver default effort level if unset.</span></div>
<divclass="line"><aid="l00300"name="l00300"></a><spanclass="lineno"> 300</span><spanclass="comment">// Effort on getting a stronger LP relaxation (MIP only) or the solver default</span></div>
<divclass="line"><aid="l00301"name="l00301"></a><spanclass="lineno"> 301</span><spanclass="comment">// effort level if unset.</span></div>
<divclass="line"><aid="l00303"name="l00303"></a><spanclass="lineno"> 303</span><spanclass="comment">// NOTE: disabling cuts may prevent callbacks from having a chance to add cuts</span></div>
<divclass="line"><aid="l00304"name="l00304"></a><spanclass="lineno"> 304</span><spanclass="comment">// at MIP_NODE, this behavior is solver specific.</span></div>
<divclass="line"><aid="l00307"name="l00307"></a><spanclass="lineno"> 307</span><spanclass="comment">// Effort in finding feasible solutions beyond those encountered in the</span></div>
<divclass="line"><aid="l00308"name="l00308"></a><spanclass="lineno"> 308</span><spanclass="comment">// complete search procedure (MIP only), or the solver default effort level if</span></div>
<divclass="line"><aid="l00312"name="l00312"></a><spanclass="lineno"> 312</span><spanclass="comment">// Effort in rescaling the problem to improve numerical stability, or the</span></div>
<divclass="line"><aid="l00313"name="l00313"></a><spanclass="lineno"> 313</span><spanclass="comment">// solver default effort level if unset.</span></div>
<divclass="ttc"id="anamespaceoperations__research_html"><divclass="ttname"><ahref="namespaceoperations__research.html">operations_research</a></div><divclass="ttdoc">Collection of objects used to extend the Constraint Solver library.</div><divclass="ttdef"><b>Definition:</b><ahref="dense__doubly__linked__list_8h_source.html#l00021">dense_doubly_linked_list.h:21</a></div></div>
