Statements (44)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Combinatorial Optimization Problem
|
| gptkbp:appliesTo |
Textile industry
Paper industry Metal industry Wood industry |
| gptkbp:category |
gptkb:Mathematical_Programming
Optimization Resource Allocation Industrial Applications |
| gptkbp:describes |
Minimizing waste when cutting raw materials
|
| gptkbp:field |
gptkb:Mathematics
Industrial Engineering Operations Research |
| gptkbp:formedBy |
1961
Gilmore and Gomory |
| gptkbp:generalizes |
Multi-dimensional Cutting Stock Problem
One-dimensional Cutting Stock Problem Two-dimensional Cutting Stock Problem |
| https://www.w3.org/2000/01/rdf-schema#label |
Cutting Stock Problem
|
| gptkbp:notableFor |
gptkb:Dynamic_Programming
gptkb:Greedy_Algorithm gptkb:Integer_Programming gptkb:Simulated_Annealing gptkb:Genetic_Algorithm Tabu Search Branch-and-Price Gilmore-Gomory Algorithm |
| gptkbp:notablePublication |
A Linear Programming Approach to the Cutting-Stock Problem (Gilmore & Gomory, 1961)
|
| gptkbp:objective |
Meet demand for smaller pieces
Minimize trim loss |
| gptkbp:prohibits |
Demand for each item
Raw material length |
| gptkbp:relatedTo |
gptkb:Knapsack_Problem
gptkb:Bin_Packing_Problem |
| gptkbp:solvedBy |
gptkb:Metaheuristics
Heuristics Linear Programming Column Generation |
| gptkbp:type |
NP-hard problem
|
| gptkbp:usedIn |
gptkb:Logistics
Manufacturing Production Planning |
| gptkbp:bfsParent |
gptkb:Integer_Programming
|
| gptkbp:bfsLayer |
6
|