Submitter Variables Constraints Density Status Group Objective MPS File
Nora Konnyu 68865 2565 3.23528e-03 hard gmu -14180699.047 gmut-75-50.mps.gz

Timber harvest scheduling model. Solved by ParaXpress in a 12288 core supercomputer run on HLRN III. 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 68865 35915
Constraints 2565 2565
Binaries 68859 35909
Integers 0 0
Continuous 6 6
Implicit Integers 0 0
Fixed Variables 0 0
Nonzero Density 0.00323528 0.00620076
Nonzeroes 571475 571226
Constraint Classification Properties
Original Presolved
Total 2565 2565
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 0 0
Precedence 0 0
Variable Bound 18 18
Set Partitioning 0 0
Set Packing 2540 2540
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 0.7781512
Constraint % 0.0779727 0.140351 0.0779727 0.3898640
Variable % 0.0055700 0.007800 0.0055700 0.0167061
Score 0.0070170

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 -14180418 -14180418 0 0 0 - 2018-10-12 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to gmut-75-50 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 Variables Binaries Integers Continuous Constraints Nonz. Submitter Group Status Objective
gmut-76-50 68865 68859 0 6 2586 470045 Nora Konnyu gmu open -14171397.828*
gmut-76-40 24338 24332 0 6 2586 153017 Nora Konnyu gmu open -14169441.78*
gmu-35-50 1919 1914 0 5 435 8643 Nora Konnyu gmu easy -2607958.33
gmu-35-40 1205 1200 0 5 424 4843 Nora Konnyu gmu easy -2406733.3688
supportcase31 488882 488760 0 122 26195 1833860 Domenico Salvagnin open -3720089.081*

Reference

No bibliographic information available

Last Update Nov 19, 2018 by Gregor Hendel
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