INTEGRATED OPTIMIZATION OF FUNCTIONAL
AND LAYOUT DESIGNS BASED ON GENETIC ALGORITHM
Consideration of Carbon Emission troughout Product’s Lifecycle
Masakazu Kobayashi and Masatake Higashi
Toyota Technological Institute, 2-12-1 Hisakata, Tempaku, Nagoya, Japan
Keywords: Design optimization, Conceptual design, Lifecycle assessment, Functional design, Layout design,
Hierarchical optimization, Genetic algorithm.
Abstract: In our previous research, the integrated optimization of functional / layout designs based on genetic
algorithm was developed for supporting conceptual design phase. This method can optimize a functional
structure and a parts layout simultaneously by evaluating performance, cost and size. In this paper, we now
focus on consideration of lifecycle characteristics in response to rise of environmental awareness in recent
years and combine our previous integrated method with lifecycle assessment (LCA) in order to enable
creation of product concepts that balance various characteristics including lifecycle ones at a higher level.
This paper also shows an application of the proposed method to a personal computer design and discusses
the effect of consideration of lifecycle characteristics during conceptual optimization.
1 INTRODUCTION
Due to rise of environmental awareness in recent
years, companies are required to assess and improve
various product lifecycle characteristics such as
carbon emission. To evaluate them, ISO14040
series, which describe the principles and framework
for LCA, were established and various commercial
LCA software such as GaBi, SimaPro and JEMAI
LCA pro was developed. However, since not only
lifecycle characteristics but also product’s primary
ones such as performance, cost and size need to be
simultaneously considered for creating an attractive
product, designers are forced to take a great deal of
time and effort to balance them at a higher level.
Based on the above background, this paper
proposes a new integrated optimization method for
creating product concepts that balance various
characteristics including lifecycle ones at a higher
level, based on our integrated optimization method
(Kobayashi, Suzuki and Higashi, 2009). Our
previous method is the integration of functional /
layout optimization based on genetic algorithm for
supporting a conceptual design phase. During a
conceptual design phase, since there are various
decision-makings, designers are asked to make
optimal decisions to create great product concepts by
considering various valuation characteristics such as
performance, cost and size. However, since
functional / layout designs, which are main two tasks
of a conceptual design phase, are very different tasks,
their design problems are highly hierarchized and
their solution spaces are vast, it is extremely difficult
for designers to build up great concepts only with
their own decision makings. To overcome such
difficulty, functional / layout optimization are
combined and executed cooperatively in our method.
Using this method, both a functional structure and a
parts layout that satisfy various characteristics at a
high level can be obtained. The method proposed in
this paper is based on our previous method and LCA,
which combination enables a design of a product
concept with consideration of various characteristics
including lifecycle ones.
2 INTEGRATED OPTIMIZATION
METHOD
2.1 Overview
This paper proposes an integrated method for
optimizing a functional structure and a parts layout
by considering various characteristics including
344
Kobayashi M. and Higashi M..
INTEGRATED OPTIMIZATION OF FUNCTIONAL AND LAYOUT DESIGNS BASED ON GENETIC ALGORITHM - Consideration of Carbon Emission
troughout Product’s Lifecycle.
DOI: 10.5220/0003077203440347
In Proceedings of the International Conference on Evolutionary Computation (ICEC-2010), pages 344-347
ISBN: 978-989-8425-31-7
Copyright
c
 2010 SCITEPRESS (Science and Technology Publications, Lda.)

lifecycle ones, based on our previous method.
Improved point is to integrate lifecycle assessment
in order to consider its results as one of valuation
characteristics of the integrated optimization.
Figure 1 shows the overview of the proposed
integrated optimization method. As shown in this
figure, this method consists of functional / layout
optimization plus LCA. Functional optimization is
the main part of the proposed method and executed
just one time. Functional optimization is based on
the hierarchical genetic algorithm (HGA)
(Yoshimura and Izui, 2002) in order to consider
hierarchical nature of a functional structure. In the
proposed method, performance, cost, total area and
total carbon emission are considered as valuation
characteristics of the functional optimization. Any of
them can be configured as an objective function and
the rest of them are configured as constraint
conditions. The proposed method assumes that
performance and cost can be calculated by simply
summing up the values associated with each part,
whereas total area and total carbon emission can not
be calculated by simple summation. Therefore,
layout optimization and LCA are repeatedly invoked
from the functional optimization to obtain the layout
with minimum area and total carbon emissions
respectively for every design proposal and for every
generation of the functional optimization. Layout
optimization is based on the traditional genetic
algorithm and the sequence-pair representation
(Murata, Fujiyoshi, Nakatake, and Kajitani, 1996).
Generation of solutions
Evaluation of solutions
Layout optimization
using GA
S
o
l
u
t
i
o
n
C
a
r
b
o
n
e
m
i
s
s
i
o
n
S
o
l
u
t
i
o
n
C
a
r
b
o
n
e
m
i
s
s
i
o
n
Iteration
•Performance
•Carbon emission
•Cost
•Area
(Selection, crossover, mutation)
Functional optimization using HGA
Optimal solution
Functional structure including alternatives
•Optimal functional structure
•Optimal layout
Lifecycle assessment
S
o
l
u
t
i
o
n
O
p
t
i
m
a
l
la
y
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u
t
A
r
e
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S
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l
u
t
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o
n
O
p
t
i
m
a
l
la
y
o
u
t
A
r
e
a
Area
Figure 1: Overview of the integrated optimization.
Due to space limitation, the following section
only describes the part of LCA. See the reference
(Kobayashi, Suzuki and Higashi, 2009) for the
details of functional / layout optimization and their
integration.
2.2 Lifecycle Assessment
In the practical LCA, there are various valuation
characteristics such as emissions of CO2, SOx and
NOx throughout entire product’s lifecycle, usage
rate of renewable material and reuse / recycle rate.
This paper adopts carbon emission as a valuation
characteristic of the propsoed method, because CO
2
reduction is one of most interested problems in order
to fight global warming in recent years. Total carbon
emission of each design proposal obtained during
functional optimization processes is calculated by
the following concepts.
(a) Value of carbon emissions is evaluated and
configurated for each part by executing LCA.
(b) All parts can be classified into two types. One
has the fixed value of carbon emissions and the other
has the value of carbon emissions per unit area.
Most parts belong to the former type, whereas an
electronic substrate, for example, belongs to the
latter type. Actual value of carbon emissions of the
latter type is calculated by multiplying unit carbon
emissions by the area calculated by layout
optimization.
(c) Total carbon emission of a design proposal
GHG
total
is defined by the below equation.



n
j
jj
m
i
itotal
uGHGAreaGHGGHG
11
(1)
Where GHG
i
is the fixed value of carbon emissions
of part i, whereas, uGHG
j
is the value of carbon
emissions per unit area of part j. Area
j
is the value of
area of part j.
3 CASE STUDY
3.1 Problem Description
In the case study, internal devices of a personal
computer are designed using the proposed method .
“Internal devices” means that input devices, a
display and an enclosure are not included.
A computer consists of the following 5
components: motherboard, HDD, cooling system,
power supply and auxiliary storage. Motherboard,
cooling system and power supply can be
decomposed into more than one part, whereas HDD
and auxiliary storage can not be decomposed any
more. Table 1 shows an example of their alternatives.
Prices and sizes are configured by surveying their
retail price and measuring their size. Performances
INTEGRATED OPTIMIZATION OF FUNCTIONAL AND LAYOUT DESIGNS BASED ON GENETIC ALGORITHM -
Consideration of Carbon Emission troughout Product's Lifecycle
345

Supply
Power
Read/Write
Outer information
Process
Information
Storage
Inter information
Battery
Optical drive
Memory card
reader
HDD
Process
Information
Personal ComputerPersonal Computer
DVD combo
Super multi A
Super multi B
DVD combo
Super multi A
Super multi B
SD memory reader
CF memory reader
SD memory reader
CF memory reader
Motherboard B
Power supply
Discard
Heat
Cooler
Control
Power
Controller
Convert Electric
power to Torque
Motor
Generate
Wind
Fan
80mm Fan
120mm Fan
Convert Electric
power to Torque
Motor
Generate
Wind
Fan
80mm Fan
120mm Fan
Process
Information
Store Data
Transfer
Data
Other
functions
Chipset
Atom Z530
Atom Z520
Atom Z540
Atom Z530
Atom Z520
Atom Z540
DDR2-533 1G
DDR2-533 2G A
DDR2-533 2G B
DDR2-533 1G
DDR2-533 2G A
DDR2-533 2G B
Support
communication
Motherboard A
WLAN module A
WLAN module B
Support Wireless
communication
WLAN module
TV tuner A
TV tuner B
Receive TV
TV tuner
Other
functions
Other
devices
WLAN module A
WLAN module B
Support Wireless
communication
WLAN module
TV tuner A
TV tuner B
Receive TV
TV tuner
Other
functions
Other
devices
Other
devices
Other
devices
Sub-boardDIMMCPU
MK8009GAH
WD1600BEVT
WD5000AAKB
MK8009GAH
WD1600BEVT
WD5000AAKB
MK1214GAH
WD3200BEVT
WD1002FBYS
MK1214GAH
WD3200BEVT
WD1002FBYS
Lithium polymer A,B
Lithium ion A,B
Discard
Heat
Cooling system
Remove
Heat
Convey
Heat
Cooler
Heat pipe
Radiation sheet
Generate
Wind
Motor
Fan
40mm Fan
60mm Fan
80mm Fan
Convert Electric
power to Torque
Generate
Wind
Motor
Motor FanFan
40mm Fan
60mm Fan
80mm Fan
Convert Electric
power to Torque
Sheet A
Sheet B
Figure 2: Functional structure designed in the case study.
are subjectively and intuitively configured.
Carbon emissions are configured by surveying the
reference (Japan Environmental Management
Association For Industry, 2007). Figure 2 shows the
functional structure of a personal computer used
here. Note that, due to space limitation, the lower
functional structure of Motherboard B is not
described here. Motherboard B is similar to
Motherboard A, but has powerful CPU, more
Memory and discrete graphic card.
In the case study, performance is handled as an
objective function, whereas cost, total area and total
carbon emission are handled as constraint conditions.
Table 1: Examples of parts specifications.
Cost
(USD)
Dimension
(cm)
Perfor
mance
CO
2
(kg)
SD memory reade
r
25 2.4*3.2 3 0.13
CF memory reader 130 4.3*3.6 2 0.27
CD-R/RW/DVD combo 80 12.8*13.0 7 2.87
Super multi drive A 130 12.8*13.0 8 2.87
Super multi drive B 260 12.8*13.0 10 2.87
3.2 Results
Figure 3 shows the results from the use of our
previous method that does not consider carbon
emission. In this case, optimizations ars executed 12
times under 12 various cost constraints from 550
USD to 2550 USD and constant area constraint
(Area < 1200 cm
2
). Parameters of HGA and GA are
shown in Tabel 2. The optimal layouts of the design
solutions denoted by two stars in Figure 3 are shown
in Figure 4. Whereas, Figure 5 shows the result from
the use of the proposed method that considers
carbon emission. In this case, optimizations are also
executed 12 times under 12 various constraints of
carbon emission from 5 kg to 50 kg and constant
constraints (Cost < 3000 USD and Area < 1500 cm
2
).
Parameters of HGA and GA shown in Table 2 are
also used in this case.
Table 2: Parameters of HGA and GA.
HGA GA
Population 100 60
Crossover rate 1 1
Mutation rate 0.05 0.01
Generation gap 0.9 0.5
Terminal generation 200 50
0
20
40
60
80
100
120
500 1000 1500 2000 2500 3000
Cost
Performance
Figure 3: Relationships between performance and cost of
obtained solutions.
ICEC 2010 - International Conference on Evolutionary Computation
346

Battery
Cooling
system
HDD
Card reader
Motherboard
240mm
174mm
Motherboard
HDD
Cooling
system
Power supply
Optical
drive
240mm
4
35
mm
Figure 4: Optimal layouts (Left: Star 1, Right: Star 2).
0
20
40
60
80
100
120
0 102030405060
Carbon emission
Performance
Figure 5: Relationships between performance and carbon
emission of obtained solutions.
A Comparison between two results shows that a
constraint of carbon emission makes it difficult to
design a high performance PC even if constraints of
cost and area are sufficiently relaxed. This is
because high performance parts used in the case
study have a tendency to emit a lot of CO
2
throughout their lifecycle. These results show that
the proposed method can obtain a optimal product
concept with consideration of various characteristics
including carbon emission.
4 CONCLUSIONS
To create optimum product concepts that balance
product primary characteristics such as performance
and cost and product lifecycle ones such as carbon
emissions at a higher level in response to rise of
environmental awareness in recent years, this paper
combines LCA with our previous method that
integrates functional / layout optimization. Using the
proposed method, optimal functional structure and
parts layout can be obtained by considering various
characteristics including lifecycle ones. Although
consideration of lifecycle characteristics are
indispensable in recent product development, not
only lifecycle characteristics but also product’s
primary ones such as performance and cost need to
be simultaneously considered and balanced at a
higher level for creating an attractive product. This
is why the proposed method is quite useful.
In the case study, the proposed method is applied
to a design of a personal computer and the results
show the effect of consideration of lifecycle
characteristics during conceptual design phase.
As for future works, we are planning to improve
the following points.
(1) For practical products, since connections
between components or parts have crucial roles such
as force transmission and object transport, their
consideration is the first issue to be settled.
(2) For practical products, since parts have many
different appearances and are placed in 3D space,
consideration of a three-dimensional layout with
arbitrary part shape is required to extend the range of
application of the proposed method.
(3) In the proposed method, only carbon emission is
considered. Consideration of lifecycle characteristics
in addition to carbon emission will improve the
effectiveness of the proposed method.
ACKNOWLEDGEMENTS
This study was supported in part by a grant of
Strategic Research Foundation Grant-aided Project
for Private Universities from Ministry of Education,
Culture, Sport, Science, and Technology, Japan
(MEXT), 2008-2012 (S0801058).
REFERENCES
Yoshimura, M. and Izui, K. (2002). Smart Optimization of
Machine Systems Using Hierarchical Genotype
Representations. Transaction of ASME, Journal of
Mechanical Design, 124, 375-384.
Kobayashi, M., Suzuki, Y. and Higashi, M. (2009).
Integrated Optimization for Supporting Functional and
Layout Designs during Conceptual Design Phase.
Proceedings from IDETC/CIE 2009: ASME 2009
International Design Engineering Technical
Conferences & Computers and Information in
Engineering Conference, San Diego, CA.
Murata, H., Fujiyoshi, K., Nakatake, S. and Kajitani, Y.
(1996). VLSI Module Placement Based on Rectangle-
Packing by the Sequence-Pair. IEEE Transactions on
Computer-Aided Design of Integrated Circuits and
Systems, 15(12), 1518-1524.
Japan Environmental Management Association for
Industry (2007). Implementation manual of product
LCA.
INTEGRATED OPTIMIZATION OF FUNCTIONAL AND LAYOUT DESIGNS BASED ON GENETIC ALGORITHM -
Consideration of Carbon Emission troughout Product's Lifecycle
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