Adjacency – Based Heuristic for Facilities Design
Ornurai Sangsawang and Sunarin Chanta
Department of Industrial Management
Faculty of Technology and Industrial Management
King Mongkut’s Institute of Technology North Bangkok
1518 Pibulsongkram Rd., Bangsue, Bangkok 10800, Thailand
Phone / Fax: 6637 213 367 Ext. 7042 Email: oss@kmitnb.ac.th
Abstract
This article presents a new construction algorithm for
computer – aided plant layout. A case study is an assembly
plant which will be expanded to construct a new plant. The
layouts are generated by ALDEP and Adjacency – Based
Heuristic that are evaluated by the maximize adjacency –
based objective. The solution will be developed on the basis of
mathematical expressions that can be evaluated objectively.
For the results, found that the layout generated from
Adjacency – Based Heuristic has the layout score better than
the layout is generated by ALDEP, and Adjacency – Based
Heuristic can generate the material handling distance less
than the layout is generated by ALDEP.
2. Method
Maximize adjacency – based objective. That considers
the adjacency score is computed from the sum of all
relationship values which considers the adjacency departments
only.
m = the number of departments
wrij = weight for the adjacency class, corresponding to
the relationship chart
(A = 64 , E = 16 , I = 4 , O = 1 , U = 0)
daij = adjacency distance from department i to department
j
daij = 1; department i and department j are adjacency
daij = 0 ; department i and department j are not adjacency
Keywords : Computer – aided plant layout , ALDEP,
Adjacency – Based Heuristic, construction algorithm,
Facilities Design.
1. Introduction
Modern industries have rapidly developed manufacturing
system. The layout design is an important task when a
manufacturing system is constructed, or expanded. If the
facilities are arranged optimally, manufacturers can decrease
work – in – process, material-handling costs, total production
costs and significantly enhance a system’s efficiency.
Computer – aided plant layout has several advantages.
The computer can perform the calculations and generate
several solutions much more accurately than manual
procedures and the solutions will be developed on the basis of
mathematical expressions that can be evaluated objectively.
Facilities design has the major objective of cost
minimization, and the material handling cost can be reduced by
placement closely related facilities. A good layout leads to
reducing production costs, and increasing productivity.
Construction layout algorithm is the important procedure to
generate a layout in the first time. There are varieties of
selection and placement procedures in several construction
algorithms. Each algorithm has the suitable objective for itself
such as minimize distance – weighted adjacency – based
objective , maximize adjacency – based objective to maximize
closeness.
2.1 Selection procedure
The first department is selected to enter the layout from
the department having the lowest Total Closeness Rating
(TCR). The second department is selected from the department
having strongest relationship with the first selected department
to be a victor. Then, select the next department from the
department that has the highest important relationship (A or E)
with the victor. If no departments have the important
relationship with the victor, the next department to enter the
layout will be selected by consideration the highest sum of
relationship between the department and all the selected
departments. This process continues until all departments have
been selected to enter the layout.
From the relationship chart in figure 1, department 1 has
the lowest TCR, it is the first to enter. The next department,
which has the strongest relationship with the first selected
department, is department 2.Then, search for the highest
important relationship with department 2, and there is not
found.
Later, try to find the highest sum of relationship among all the
unselected departments and the unselected departments. Found
that department 3 has the highest sum of relationship with
department 1 and department 2. Thus, the next victor is
department 3. Then, Department 4 is selected from the highest
relationship with department 3 to be the next victor. Selection
Proceedings of the International Conference on Computer and Industrial Management, ICIM, October 29-30, 2005, Bangkok, Thailand
15.1
of the next department depends on the highest important
relationship that it has with the previously selected department.
The overall order of departments entering the layout is 1-2-3-48-9-10-7-6-5.
Figure 3 the layout generated from ALDEP algorithm
Table 1 layout score computation of the layout from ALDEP
algorithm
2.2 Placement procedure
Placement procedure begins by placing the first
department which derived from selection procedure in the
right-downside corner of the layout. And placing the next
departments uses the placing rating that is the sum of the
weighted closeness ratings (A=243, E = 81, I = 27, O = 9, U =
1, X = -729) between the entering department and its new
neighbors. The next departments are entered at that location
with the largest placing rating.
Adjacency
Department
1-2
1-3
1-4
Relationship
E
I
U
Score
16
4
0
1-9
2-10
3-4
3-9
5-6
5-8
U
U
E
U
A
U
0
0
16
0
64
0
6-7
6-8
7-8
7-10
8-9
9-10
A
I
A
U
A
A
64
4
64
0
64
64
Total score
Figure 1 the relationship chart for electronic printed circuit
board
As a result, the layout is generated by Adjacency Based Heuristic, which is displayed in the figure 4. The ordinal
selected departments are 1-2-3-4-8-9-10-7-6-5.
The layout score is 373.
3. Results
In the case study created a new layout for electronic printed
circuit board by using ALDEP and Adjacency – Based
Heuristic. The plant layout was generated by ALDEP which
the ordinal selected departments are 5-6-7-8-9-10-2-1-3-4. By
referencing maximize adjacency – based objective. The layout
score is equal to 360.
the minimize distance – weighted adjacency – based objective,
the layout is displayed in the figure 3.
5
5
8
8
9
9
3
3
4
4
5
5
8
8
9
9
3
3
4
4
5
5
8
8
9
9
1
1
4
4
5
5
8
8
9
9
1
1
4
4
6
6
8
8
9
9
1
1
6
6
8
8
9
9
1
1
6
6
7
7
10
10
2
2
6
6
7
7
10
10
2
2
360
Special Issue of the International Journal of the Computer, the Internet and Management, Vol. 13 No.SP2, October, 2005
15.2
Start
Read the input data
- Relationship chart
- each department areas
Define the selected dep.
as the winner
Select the department
having the lowest TCR
department
Select the department
having the strongest
Rel. with the winner
Are the dep. have
the highest‘Important’
Rel. with the victor ?
Define the selected dep.
as the victor
y
Select the dep. having
the highest‘Important’
Rel. with the victor
n
Are the dep. have
the highest ‘Important’ Rel.
with all
the selected deps. ?
Define the next victor
n
y
Select the dep. having
the highest‘Important’
Rel. with all the
selected deps.
Are all the dep.
already
selected ?
Figure 2 Flowchart
for Computer Aided
Layout Planning
with Department
Relationship
y
Placement Procedure
n
Calculate the sum of the
Rel. with all the selected
departments
Display the layout
Compute
the layout score
Select the highest sum of
the Rel. with all the selected
departments
End
Proceedings of the International Conference on Computer and Industrial Management, ICIM, October 29-30, 2005, Bangkok, Thailand
15.3
5
5
7
7
8
8
4
4
4
4
5
5
7
7
8
8
4
4
4
4
place at the right – downside corner of the layout. Similarity,
ALDEP focuses on the strongest relationship with the
immediately previously selected department, and so does
Adjacency-Based Heuristic. If no departments have the
important relationship with the selected department, ALDEP
procedure will randomly select the next department while
Adjacency-Based Heuristic will be selected by consideration
the highest sum of relationship between the department and all
the selected departments.
5
5
6
6
8
8
3
3
2
2
5. Suggestion
5
5
6
6
8
8
3
3
2
2
6
6
8
8
1
1
1
1
6
6
8
8
1
1
1
1
5.1 Adjacency-Based Heuristic is a construction algorithm that
can reasonably generate a good layout, but it cannot
confirm that the layout which found is the optimal layout.
5.2 Adjacency-Based Heuristic operates faster than ALDEP
algorithm, which randomly generate several times and
many layouts until the good layout is constructed.
5.3 The reality objectives for facilities design such as
flexibility and safety should be considered.
10 10 9
9
9
9
9
9
10 10 9
9
9
9
9
9
Figure 4 the layout generated from the Adjacency – Based
Heuristic
Table 2 layout score computation of the layout from
Adjacency – Based Heuristic
6. References
D.R. Sule (1998), Manufacturing Facilities Location, Planning,
and Design: International Thomson Publishing
Adjacency
Department
1-2
1-3
1-8
2-3
Relationship
E
I
U
O
Score
16
4
0
1
2-4
3-4
3-8
4-9
4-8
5-6
U
E
U
U
E
A
0
16
0
0
16
64
5-7
6-7
6-8
7-8
8-9
9-10
U
A
U
A
A
A
0
64
0
64
64
64
Total score
Edwards, H.K., Gillett., and Hale, M.C. (1970). Modular
Allocation Technique; MAT. Management Science, Vol. 17,
161-169.
Heragu Sunderesh (1997). Facilities design. Imprint Boston:
PWS Publishing Company.
Tompkins, James A., and James M. Moore (1977). Computer
Aided Layout: A User’s Guide. American Institute of
Industrial Engineers, Norcross, GA.
373
4. Conclusion
From the results as shown in the table 1 and the table 2, found
that the layout generated from Adjacency – Based Heuristic
has the layout score better than the layout generated from
ALDEP.
In the selection procedure of Adjacency – Based
Heuristic, to reduce the opportunity which the edge area of the
lowest TCR department will be adjoined with the other
departments. The lowest TCR department is firstly selected to
Special Issue of the International Journal of the Computer, the Internet and Management, Vol. 13 No.SP2, October, 2005
15.4