gmut-76-40

variable_bound set_packing mixed_binary

Submitter Variables Constraints Density Status Group Objective MPS File
Nora Konnyu 24338 2586 2.43123e-03 open gmu -14169441.78* gmut-76-40.mps.gz

Timber harvest scheduling model These are harvest scheduling models of hypothetical forest planning problems where net timber revenues are maximized over a planning horizon subject to four sets of constraints: 1. Each management unit can be harvested only once over the planning horizon, 2. Volume harvested in one planning period should not be less or more than some portion of that in the preceding period, 3. Area-weighted average age of the forest by the end of the plan should notbe less than a certain target age. 4. Clearcut size in any planning period has to be below a specific limit. Decision variable are management units and generalized management units (group of management units with a combined area not exceeding the limit on clearcut size) and can be either fully harvested or left untouched in any planning period, therefore there is a binary restriction on the decision variables. Imported from the MIPLIB2010 submissions.

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 24338 12402
Constraints 2586 2586
Binaries 24332 12396
Integers 0 0
Continuous 6 6
Implicit Integers 0 0
Fixed Variables 0 0
Nonzero Density 0.00243123 0.00476275
Nonzeroes 153017 152749
Constraint Classification Properties
Original Presolved
Total 2586 2586
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 0 0
Precedence 0 0
Variable Bound 14 14
Set Partitioning 0 0
Set Packing 2565 2565
Set Covering 0 0
Cardinality 0 0
Invariant Knapsack 0 0
Equation Knapsack 0 0
Bin Packing 0 0
Knapsack 0 0
Integer Knapsack 0 0
Mixed Binary 7 7
General Linear 0 0
Indicator 0 0

Structure

Available nonzero structure and decomposition information. Further information can be found here.

value min median mean max
Components 0.602060
Constraint % 0.0773395 0.1804590 0.0773395 0.3866980
Variable % 0.0161264 0.0295651 0.0241896 0.0483793
Score 0.005412

Best Known Solution(s)

Find solutions below. Download the archive containing all solutions from the Download page.

ID Objective Exact Int. Viol Cons. Viol Obj. Viol Submitter Date Description
1 -14169442 -14169442 5e-07 1e-06 0 - 2018-10-13 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to gmut-76-40 in the collection. This similarity analysis is based on 100 scaled instance features describing properties of the variables, objective function, bounds, constraints, and right hand sides.

Instance Status Variables Binaries Integers Continuous Constraints Nonz. Submitter Group Objective Tags
gmut-76-50 open 68865 68859 0 6 2586 470045 Nora Konnyu gmu -14171893.7789212* variable_bound set_packing mixed_binary
gmut-75-50 hard 68865 68859 0 6 2565 571475 Nora Konnyu gmu -14180699.047 variable_bound set_packing mixed_binary
gmu-35-50 easy 1919 1914 0 5 435 8643 Nora Konnyu gmu -2607958.33 benchmark benchmark_suitable variable_bound set_packing mixed_binary
gmu-35-40 easy 1205 1200 0 5 424 4843 Nora Konnyu gmu -2406733.3688 benchmark benchmark_suitable variable_bound set_packing mixed_binary
supportcase31 open 488882 488760 0 122 26195 1833861 Domenico Salvagnin -3720089.081* decomposition numerics precedence set_packing invariant_knapsack knapsack mixed_binary

Reference

No bibliographic information available

Last Update Mar 04, 2024 by Julian Manns
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