1 Introduction 2 How to Run a Model with OSL

OSL 11Option Description Defaultstrategy MIP strategy for deciding branching.None1: Perform probing only on satisfied 0-1 variables. This is the default settingin OSL. When a 0-1 variable is satisfied, OSL will do probing to determinewhat other variables can be fixed as a result. If this bit is not set, OSL willperform probing on all 0-1 variables. If they are still fractional, OSL willtry setting them both ways and use probing to build an implication list foreach direction.2: Use solution strategies that assume a valid integer solution has been found.OSL uses different strategies when looking for the first integer solution thanwhen looking for a better one. If you already have a solution from a previousrun and have set a cutoff value, this option will cause OSL to operate asthough it already has an integer solution. This is beneficial for restartingand should reduce the time necessary to reach the optimal integer solution.4: Take the branch opposite the maximum pseudo-cost. Normally OSL willbranch on the node whose smaller pseudo-cost is highest. This has theeffect of choosing a node where both branches cause significant degradationin the objective function, probably allowing the tree to be pruned earlier.With this option, OSL will branch on the node whose larger pseudo-cost ishighest. The branch taken will be in the opposite direction of this cost. Thishas the effect of forcing the most nearly integer values to integers earlier andmay be useful when any integer solution is desired, even if not optimal. Herethe tree could potentially grow much larger, but if the search is successfuland any integer solution is adequate, then most of it will never have to beexplored.8: Compute new pseudo-costs as variables are branched on. Pseudo-costs arenormally left as is during the solution process. Setting this option will causeOSL to make new estimates, using heuristics, as each branch is selected.16:Compute new pseudo-costs for unsatisfied variables. Pseudo-costs are normallyleft as is during the solution process. Setting this option will causeOSL to make new estimates, using heuristics, for any unsatisfied variables’pseudo-costs in both directions. This is done only the first time the variableis found to be unsatisfied. In some cases, variables will be fixed to a boundby this process, leading to better performance in the branch and boundroutine. This work is equivalent to making two branches for every variableinvestigated.32:Compute pseudo-costs for satisfied variables as well as unsatisfied variables.Here, if 16 is also on, OSL will compute new estimated pseudo-costs for theunsatisfied as well as the unsatisfied ones. Again, this is very expensive, butcan improve performance on some problems.strategy can be a combination of the above options by adding up the valuesfor the individual options. 48 for instance will select 16 and 32.Target Target value for the objective. 5% worsethan therelaxedsolutionthreshold Supernode processing threshold. Range [0.0, maxreal] 0tolpinf Primal infeasibility tolerance. Row and column levels less than this values 1e-8outside their bounds are still considered feasible. Range: [1e-12,1e-1].toldinf Dual infeasibility tolerance. Functions as optimality tolerance for primal simplex.1e-7Range: [1e-12,1e-1].tolint Integer tolerance Range - [1.0e-12, 1.0e-1] 1.0e-6workspace Memory allocation. Overrides the memory estimation and the workspace modelsuffix. Workspace is defined in Megabytes.None