rfds-4-days

numerics aggregations mixed_binary general_linear

Submitter Variables Constraints Density Status Group Objective MPS File
Dan Neiman 2184028 1766257 2.7128e-06 open -1101300.6521* rfds-4-days.mps.gz

Flight scheduling model, anonymized. The most prominent aspect of this model is that it attempts to find an optimal schedule for a small (14) fleet of planes over a four day period, broken down into 96 hourly periods. Planes have 14 states (in-flight, or at one of 13 locations). Goal is to satisfy passenger demand with minimal cost and minimal violation of priority requests. Takes a considerable length of time (2+ hours) to find first integer solution using CPLEX.

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 2184028 1536989
Constraints 1766257 1333421
Binaries 190080 184943
Integers 0 3822
Continuous 1993948 1348224
Implicit Integers 0 3822
Fixed Variables 27942 0
Nonzero Density 2.71280e-06 3.19785e-06
Nonzeroes 10464800 6553850
Constraint Classification Properties
Original Presolved
Total 1766257 1333421
Empty 0 0
Free 0 0
Singleton 88071 0
Aggregations 1069032 1038078
Precedence 3072 0
Variable Bound 1746 0
Set Partitioning 0 0
Set Packing 0 0
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 604336 291521
General Linear 0 3822
Indicator 0 0

Structure

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

value min median mean max
Components
Constraint %
Variable %
Score

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 -1101301 0 1e-07 0 - 2018-10-12 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to rfds-4-days 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
neos-4545615-waita open 654950 654930 0 20 345152 10670200 Jeff Linderoth neos-pseudoapplication-31 no_solution aggregations set_partitioning set_packing set_covering cardinality invariant_knapsack knapsack mixed_binary
gasprod2-1 easy 29568 7389 0 22179 73448 282846 Andrew Stamps gasprod 1628548.2968 numerics aggregations precedence variable_bound invariant_knapsack binpacking mixed_binary
neos-4562542-watut open 134705 134694 0 11 73746 2015540 Jeff Linderoth neos-pseudoapplication-31 6650* aggregations set_partitioning set_packing set_covering cardinality invariant_knapsack knapsack mixed_binary
neos-4533806-waima open 93318 93304 0 14 52983 1250570 Jeff Linderoth neos-pseudoapplication-31 4870* decomposition aggregations set_partitioning set_packing set_covering cardinality invariant_knapsack knapsack mixed_binary
neos-4555749-wards open 89147 89130 0 17 51776 1263380 Jeff Linderoth neos-pseudoapplication-31 3759* decomposition aggregations set_partitioning set_packing set_covering cardinality invariant_knapsack knapsack mixed_binary

Reference

No bibliographic information available

Last Update Mär 19, 2019 by Gregor Hendel
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