Title: Application of the Cutting Stock Problem
1- Application of the Cutting Stock Problem
- to a Construction Company A Case Study
- Seda Alp, Gurdal Ertek, S.Ilker Birbil
- Sabanci Üniversitesi
- Mühendislik ve Doga Bilimleri Fakültesi
- Orhanli, Tuzla, Istanbul, 34956
2Outline
- Introduction
- The Problem Setting
- The Company
- The 1D Cutting Stock Problem
- The Solution Approaches
- Solving within the GAMS Modeling System
- Developing an IP-based Optimization Program
- Benchmarking Results
- The Performance Data
- Insights
- A Visual Approach for Determining How to Batch
Subprojects - Conclusions
3Introduction
- The goal of the 1 Dimensional cutting stock
problem - is to find the "optimal" cutting patterns,
where the total number of long steel bars used is
minimized, subject to the constraint that the
desired shorter steel bars are cut in needed
quantities.
4Bar Length 1200 cm
..........
Bar Length 600 cm
1
..........
2
...
15
Bar Length 700 cm
Bar Length 300 cm
1
1
..........
..........
2
2
...
...
35
10
5Pattern 1
300 cm
300 cm
300 cm
300 cm
Pattern 2
300 cm
300 cm
600 cm
Pattern 3
300 cm
700 cm
Trim Loss
Pattern 4
600 cm
600 cm
6The Construction Company
- Mimag Makina Ltd
- Designs, produces, supervises formwork
- and scaffolding systems
- For structures such as dams, bridges,
- business centers, and industrial plants.
- Sample Project 1 Diesel/Kerosene
Hydroprocessing and CCR Reformer Project
implemented in Izmit Refinery of Tupras, Turkey. - Sample Project 2 Waste Water Treatment Plant
in Adana, Turkey.
7- The standard steel bars used in reinforced
concrete steel bars are 1200 cm and have various
diameters range from 6mm to 50mm.
8Tupras, Izmit
9The 1D Cutting Stock Problem
- SETS
- I set of patterns,
- J set of lengths,
- VARIABLES
- xi number of bars cut according to pattern i
- PARAMETERS
- aij number of pieces of length j within one bar
cut according to pattern i - bj required number of pieces of length j
10The Model
s.t.
- The goal of the model is
- To minimize the objective function, which
consists of the total number of long steel bars
used. - Enough number of shorter bars are cut from long
bars in required quantities. - The decision variables are restricted to
non-negative values.
11The Solution Approaches
- Solving within the GAMS Modeling System
- Gams ( http//www.gams.com )
- MS Excel
- C
- Developing an IP-based Optimization Program
- lp_solve ( http//groups.yahoo.com/group/lp_solve/
) - Java under Eclipse IDE ( http//www.eclipse.org )
- Using Commercial Software
- 1 dimensional cutting stock softwares
12BAR_LENGTH 1200 NO_OF_LENGTHS 17 LENGTHS_AND_REQU
IRED_QUANTITIES 1100 10 950 20 1200 162 350 241 93
5 147 240 48 800 96 550 147 1180 28 1020 39 830 8
875 8 1065 39 80 104 340 8 345 32 300 16
java code
datafile.txt
13results.txt
10 bars cut as 1x1100cm 20 bars cut as
1x950cm 162 bars cut as 1x1200cm 46 bars cut
as 3x350cm 68 bars cut as 1x935cm 48 bars
cut as 1x935cm 1x240cm 89 bars cut as
1x350cm 1x800cm 70 bars cut as 2x550cm 28
bars cut as 1x1180cm ... ... ... 7 bars cut
as 1x550cm 1x345cm 1x300cm
14comparison file
15Benchmarking
- Q1 How effective is our program compared to the
commercial packages that we downloaded? - Q2 How do the commercial packages compared
amongst them?
16Result - Comparison
17Insights
- None of the commercial packages have achieved the
optimal total number of bars - The software packages are not implementing an
optimal algorithm, but are implementing heuristic
techniques. - First five software packages give solutions very
close to the optimal - A construction company should choose amongst
these five software packages based on criteria
such as - price
- on-line support
- usability
- data import/export capabilities
- reporting quality (including visualization of
optimal cutting patterns and their quantities)
18Insights
- Software 6 and especially Software 7 perform
poorly. - A company should definitely avoid using Software
7, which also happens to be the most expensive
package amongst all. - Software 7 is distinguished from all others by
its capability to import/export to and from MS
Excel. - Software 6 has the best GUI amongst all packages.
- The software selection should be
- based on performance tests,
- rather than data import/export capabilities,
- GUI, or price.
19Benchmarking
- Q3 Would it be considerably more effective to
use two different software packages at the same
time for each subproject and implement the better
of the two solutions that they provide? - Q4 Does batching of two or more subprojects and
determining the best solution for the batch
increase performance (decrease the cost)?
20Benchmarking
- The software packages that perform well are
extremely close to the optimal, - there is no need to use two of those software
packages
21A Visual Approach for Determining How to Batch
Subprojects
- Subprojects can be batched (combined) to be cut
simultaneously, so that we can reduce the number
of long bars cut - As a future research, this approach can be
implemented in software packages
22Batching two projects by using Miner3D software
23Conclusions
- Result of the visual approach
- The two considered projects (Izmit and Adana) did
not include great improvement opportunities
through batching. - We even observed that batching could result in a
worse performance. - The decision maker should be aware that batching
is not always a good option. - Even though we have not gained meaningful
improvements by batching, when using our data, we
believe that for other projects there can be
significant savings. - One could especially expect good opportunities
when there are a large number of
projects/subprojects managed simultaneously, and
a large number of steel bars to be cut. - We suggest carrying out more extensive tests as a
future research area.
24Conclusion
- Available software packages should be tested with
sample project data before adoption. - Software packages with the best import/export
capabilities and/or GUI can perform very poorly. - A higher price does not guarantee a good
performance, as the worst software in our study
was also the most expensive one.
25Thank you