Complexity - Controlling chaos using cybernetics and good design

Complexity
Controlling
chaos
using
cyberne5cs
and

good
design

P.O.
Arnäs,
PhD

Per-‐Olof.Arnas@chalmers.se

@Dr_PO

Per Olof Arnäs,
Technology Management and Economics,
Division of Logistics and Transportation

What we did at work today (Rawwrrrr!) by Amit Gupta on Flickr (CC BY-NC)

What
is
a

system?
Per Olof Arnäs,

2

A
set
consists
of

more
than
one

elementary
part

Per Olof Arnäs,

3

A
set
consists
of

more
than
one

elementary
part

A
system
diﬀers
from

a
set
when
it
displays

emergent
proper,es

Per Olof Arnäs,

4

A
set
consists
of

more
than
one

elementary
part

The
whole
shows

proper5es
that
are
not

found
in
its
parts
A
system
diﬀers
from

a
set
when
it
displays

emergent
proper,es
Reduc5onism
is

not
applicable
Per Olof Arnäs,

5

A
set
consists
of

more
than
one

elementary
part

A
system
cannot
be

fully
understood
by

studying
its
parts

separately

The
whole
shows

proper5es
that
are
not

found
in
its
parts
A
system
diﬀers
from

a
set
when
it
displays

emergent
proper,es

Reduc5onism
is

not
applicable
Per Olof Arnäs,

6

A
set
consists
of

more
than
one

elementary
part

A
system
cannot
be

fully
understood
by

studying
its
parts

separately

The
whole
shows

proper5es
that
are
not

found
in
its
parts
A
system
diﬀers
from

a
set
when
it
displays

emergent
proper,es

Reduc5onism
is

not
applicable
Per Olof Arnäs,

7

Gödel´s
incompleteness
theorem

A
system
cannot
be
fully
deﬁned
from
within
Per Olof Arnäs,

8

Gödel´s
incompleteness
theorem
I
don´t

understand

I
don´t

understand

Neither
do
I

A
system
cannot
be
fully
deﬁned
from
whithin
Per Olof Arnäs,

9

I
don´t

understand

Neither
do
I

Per Olof Arnäs,
Division of Logistics and
Transportation
2009
-‐
October
-‐ NodeXL
Facebook
Network
Marc
Smith
FR
Layout
by
Marc_Smith
on
ﬂickr.com

I
don´t

understand

Important
terms

”State”
–
The
current

value
of
the
a6ributes

Si = (xi, yi, zi, vi)

”A6ributes”
–
a

collec9on
of
the

system’s
variables

(degrees
of

freedom):

e.g.
X,
Y,
Z,
V
Per Olof Arnäs,

”Trajectory”
–
a

succession
of
states
Image:
Bouncing
ball
strobe
edit,
CC-‐BY

Richard
Bartz,
Wikimedia
Commons 11

: 
tive
c

e
rsp
pe
ms
n
e
yst
atio
s
rt
The
spo
an
e tr
Th
ss
oce
pr

Goods in
initial state,
S0

Resources, R

Goods in
goal state,
S1

Transportation
system
State space, S

Trajectory =

f(S , S , R)
0

1

This process needs to be
Per Olof Arnäs,

controlled!

Conceptual
model
of
a
transportaWon
process
as
a

trajectory
between
states
(adopted
from
Hultén,
1997).

12

CO

Regulator

!
(TCS)

Input

Regulated system

!

Sy
ou ste
tp m
ut st
at
e,

G
oa

l

st

at

e

M
!
PL
Y!
T
Disturbance
EX
I
IT
EX COMPLE
!
XITY
PL
Y!
!!
M
!
!
ITY!!
O
!
COMPLEX
C
!

(transportation
system)

Feedback loop

A Transport Control System (TCS)
is a system that controls the
trajectory of a transportation
process

Per Olof Arnäs,

13

The main task

Handle complexity
Per Olof Arnäs,
Division we did at work today (Rawwrrrr!)
What of Logistics and Transportation

by Amit Gupta on Flickr (CC BY-NC)

Complexity – 3 types

Each type is associated with a specific
complexity driver
Complexity driver: A variable that indicates
increase/decrease in complexity
Per Olof Arnäs,
Division we did at work today (Rawwrrrr!)
What of Logistics and Transportation

by Amit Gupta on Flickr (CC BY-NC)

1.
Descrip9ve
complexity
Diﬃculty
in
describing

the
system
”Variety”
=
The
total
number
of

states
the
system
can
assume

(state
space)
Complexity
driver:
 
The
size
of
the
state
space
Per Olof Arnäs,

Image:
”Jan
2005
Map
of
the
Internet”
BY
ma_hewje_hall

on
ﬂickr
16

1.
Descrip9ve
complexity
Road
terminal,
local

Consignor

DomesWc

rail
terminal
Per Olof Arnäs,

DomesWc
port

Foreign
port

Consignee

Foreign

rail
terminal
17

1.
Descrip9ve
complexity
Road
terminal,
local

ed
s

e

tiv
p

ri
c

s

de

e

pl

Road
terminal,
central

om
c

ity
x

Road
terminal,
local

a

re
c

Consignor

DomesWc

rail
terminal
Per Olof Arnäs,

DomesWc
In
port

Foreign
port

Consignee

Foreign

rail
terminal
18

2.
Computa9onal
complexity
Difficulty
in
finding
the

”best”
trajectory
through

the
state
space
The
controller
needs
to
know:
a)
which
of
the
states
are
valid

Complexity
driver:
 
The
number
and
length
of

valid
trajectories
Per Olof Arnäs,

b)
which
of
the
possible

trajectories
should
be
chosen

Image:
”Playing
chess”
BY
Jeffrey
Barke
on
flickr
19

2.
Computa9onal
complexity
Road
terminal,
central
Road
terminal,
local

Consignor

?

DomesWc

rail
terminal
Per Olof Arnäs,

Road
terminal,
local

?

DomesWc
port

Foreign
port

Consignee

Foreign

rail
terminal
20

2.
Computa9onal
complexity
Road
terminal,
central
Road
terminal,
local

Consignor

?

Road
terminal,
local

?

DomesWc
port

Foreign
port

?

y
exit

l
omp
c
onal
ti
uta
p
com
d
?
ease
cr
In
?

DomesWc

rail
terminal
Per Olof Arnäs,

Consignee

Foreign

rail
terminal
21

3.
Uncertainty-‐based
complexity
Difficulty
in
describing
the

state
of
the
system

Controller
needs
to
”step
into”
the
system

during
the
preocess
to
resolve
uncertainty

Measured
by
the

informa,on
entropy
The
amount
of
informa9on

needed
to
describe
the
state
of

the
system

Complexity
driver:
 
The
number
of
decisions
that
must
be
made

during
the
transporta9on
process
Per Olof Arnäs,

Image:
”Jam
at
the
floaWng
market”

BY
Stuck
in
Customs
on
flickr
22

3.
Uncerta9nty-‐based
complexity
Road
terminal,
central
Road
terminal,
local

Consignor

✓

DomesWc

rail
terminal
Per Olof Arnäs,

✓

✓
DomesWc
port

✓

Foreign
port

Road
terminal,
local

✓

✓

✓

Consignee

Foreign

rail
terminal
23

3.
Uncerta9nty-‐based
complexity

Road
terminal,
local

Consignor

✓

Road
terminal,
central

?

✓

?

?
DomesWc
port

?

Foreign
port

?

Road
terminal,
local

?

Consignee

exity
sed compl
rtainty-ba

nce
ncreased u
I
DomesWc

rail
terminal
Per Olof Arnäs,

?

Foreign

rail
terminal
24

Cyberne9cs

Per Olof Arnäs,

?

25

Cyberne9cs

Per Olof Arnäs,

26

Cyberne9cs
Output
In

Per Olof Arnäs,

In

In

In

In

27

Cyberne9cs
Launched
as
a
branch
of

systems
science
in
the

1940´s
W
g

f
X

Mathema9cs
as
a

modelling
language

G
h

CasW's
model
of
the
input/output
relaWon

(redrawn
from
CasW,
1989,
p.
109)
Per Olof Arnäs,

Image:
”Wheldrake
sundial”
BY
Darwin70
on
ﬂickr
28

Processes
on
various
levels
(redrawn
from
NEVEM,
1989).

Per Olof Arnäs,

29

CO

Regulator

!
(TCS)

Input

Regulated system

!

Sy
ou ste
tp m
ut st
at
e,

G
oa

l

st

at

e

M
!
PL
Y!
T
Disturbance
EX
I
IT
EX COMPLE
!
XITY
PL
Y!
!!
M
!
!
ITY!!
O
!
COMPLEX
C
!

(transportation
system)

Feedback loop

A Transport Control System (TCS) is a
system that controls the trajectory of a
transportation process

Per Olof Arnäs,

30

Organize
the
trains

into
groups.
How

can
they
be

grouped?

Discuss
in
small

groups
and
try
to

ﬁnd
the
most
logical

solu9on.
Bild: Booch, 1991
Per Olof Arnäs,

31

2-‐4
wagons
7
types
of
cargo
2
types
of
wheels
2
wagon
sizes
4
wagon
types
4
wagon
roofs
Bild: Booch, 1991
Per Olof Arnäs,

32

GOAL:

Pizza Menu

Per Olof Arnäs,

33

Per Olof Arnäs,

34

Per Olof Arnäs,

35

Interface
design
In
order
to
handle
the
three
complexity
types,
a

modelling/design
process
is
needed
With
a
cyberne9c
approach,
every
system

consists
of
a
number
of
black
boxes

Each
box
is
deﬁned
by
its
interface

Per Olof Arnäs,

Image:
”MacBook
Air
by
Jony
Ive”
BY

36
marcopako

on
ﬂickr

An interface is a representation
of a system displaying its visible
state and its visible inputs.

The System

Visible 
attributes
State

Interface

Visible 
inputs

The interface hides Outbound interface
(encapsulates) 
content and function

Inbound interface

Per Olof Arnäs,

37

Dimension
1:
Interface
direcWon

Inbound interface

Per Olof Arnäs,

r
to

St

Op

The System

ate

Visible 
attributes

vec

Visible 
inputs

era

tio
ns

vec
to

r

An interface can be either
inbound or outbound

Outbound interface

Image:
”MacBook
Air
by
Jony
Ive”
BY

38
marcopako

on
ﬂickr

Dimension
2:
Interface
width
The width of the interface
consists of the number of
attributes/operations

h

idt

W

More operations – wider
interface

The System
The interface width
is reduced by

h

idt

W

More attributes (degrees of
freeedom) – wider interface

encapsulation
Per Olof Arnäs,

Image:
”MacBook
Air
by
Jony
Ive”
BY

39
marcopako

on
ﬂickr

EncapsulaWon
The System
ion
lat
psu tion
nca
c
E
un Hidden inputs
f f
o

Hidden

on
ti
la t
attributes
su ten
ap on
nc c
E
of

The System
Per Olof Arnäs,

Image:
”MacBook
Air
by
Jony
Ive”
BY

40
marcopako

on
ﬂickr

Dimension
3:
Interface
depth
The variety of each attribute and
operation together constitute the
interface depth
The depth can range from
binary to continuous

The System
Depth

The interface depth
is reduced by applying

Depth

constraints
Per Olof Arnäs,

Image:
”MacBook
Air
by
Jony
Ive”
BY

41
marcopako

on
ﬂickr

Constraints
The System
Limiting

ory
sit
ran aints
T
str
Limiting
on
c

operations

ry
na ts
states
tio ain
ta tr
S ts
on
c

The System
Per Olof Arnäs,

Image:
”MacBook
Air
by
Jony
Ive”
BY

42
marcopako

on
ﬂickr

NARROW

Few parameters

SHALLOW
Binary
parameters

Degenerated
encapsulation

Interface
WIDTH

WIDE

Many parameters
Encapsulation limits
interface width

Discreet

DEPTH

Interface

parameters
Continous
Parameters
with
constraints
Continous
Parameters

DEEP

Per Olof Arnäs,

Constraints make
interfaces more
shallow

No
encapsulation –
open system

43

Reducing
complexity
–
some
ground
rules
Exclude
variables
Diminish
state
space
Par99on
states
Group
states
into
larger

par99ons
Break
down
into
subsystems
Create
internal
interfaces
Organise
subsystems
hierarchically
Image:
”Jan
2005
Map
of
the
Internet”
BY
ma_hewje_hall
on
flickr Create
mul9ple
levels
of
abstrac9on
Image:
”Playing
chess”
BY
Jeffrey
Barke
on
flickr
Image:
”Jam
at
the
floaWng
market”
BY
Stuck
in
Customs
on
flickr
Per Olof Arnäs,

44

Key
tools
in
cyberne9cs
Black
boxes
In

In

In

In

Encapsulate
func9on
Encapsulate
content

In

Hierarchic
system

models

!

Regulated system
(transportation
system)

(TCS)

Feedback loop

Per Olof Arnäs,

Sy

!

Regulator

Input

st
em
ou
st
tp
a
ut te,

Disturbance

Control
Theory

Regulator
Trajectory
which
needs
to
be
controlled
Finite
state
space

45

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

Per Olof Arnäs,

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

46

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

By
construc9ng
the
system
from
a
number
of

black
boxes,
complexity
can
be
reduced
I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

Per Olof Arnäs,

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

47

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

By
construc9ng
the
system
from
a
number
of

classes,
complexity
can
be
reduced
I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

Per Olof Arnäs,

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

I
n

48

How
would
a

programmer

design
a
complex

system?
Per Olof Arnäs,

A
parallel
history
In
1967,
the
programming

language
Simula
67
was
launched
!
The
ﬁrst
object-‐oriented
language
!
Used
to
build
discrete
event

simula9on
models

ber
m
me
RY
e
O
R
CT
E
AJ
TR
Per Olof Arnäs,

Si = (xi, yi, zi, vi)

Discrete
event
simula9on
“…the
opera9on
of
a
system
is

represented
as
a
chronological

sequence
of
events.
Each
event
occurs

at
an
instant
in
9me
and
marks
a

change
of
state
in
the

system.”
(Wikipedia)
Image:
”Wheldrake
sundial”
BY
Darwin70
on
ﬂickr
50

The
canonical
form
of
a
complex
system
(redrawn
from
Booch,
1991).
Per Olof Arnäs,

51

Class
diagrams
1

Consignment
1..4

1
*

Pallet
-Weight
-Size
-Position
+Overpack()
+Open()
+Move()
+Fill()
+Empty()

Consignment documentation

Electronic

Physical

1
*
Order
-Consignor
-Consignee
-Customer number

Product
DG fact sheet
1

1

Sender certificate

-UN number
-Substance information
-Handling instructions
-Emergency procedures
-Contact information

Dangerous Goods Declaration

1
*

*
*

Order Item
-Type of goods
-UN number
-DG class
-Substance number
-Substance Name

Waybill item

-Product name
-UN number
-Quantity
-Packing

*

Weight

Per Olof Arnäs,

1
*

DGD item
Size

1

Waybill

-Statement
-Name
-Signature

Length

Number of pallets

Volume

52

This is the class Pallet that represents all
objects that share the same data structure.
Pallet

The topmost cell contains the name

-Height
-Width
-Depth
-Weight
The middle cell contains the attributes
-Pos-X
-Pos-Y
-Pos-Z
+MoveTo(in NewX, in NewY, in NewZ)
+LiftUp(in Distance)
+PutDown()
The bottom cell contains the
operations

A class is a template
for real-world objects
Per Olof Arnäs,

53

The class Box.

Per Olof Arnäs,

54

An object of the class Pallet can contain several objects of the class Box. The denotations 1 and * means that
one pallet (1) may contain many (*) boxes.

Per Olof Arnäs,

55

Object-‐orienta9on
is
applied
cyberne9cs!
When
looking
at
the
core
concepts
of
object-‐
orienta9on
there
is
a
clear
analogy
with
cyberne9cs

Very
few
people
have
made
that

connec9on
during
the
last
40
years!

Why?

Per Olof Arnäs,

Diﬀerent
disciplines
(Systems
science/Mathema9cs
vs

Computer
science)
Some
advances
have
been
made
towards
a
combina9on,

but
these
are
few

56
Image: Connected. 362/365 by AndYaDontStop on Flickr.com

Systems
theory

Object-‐orienta9on

System
model

↔

Object
model

State

↔

State

Outbound
(display)
interface

↔

A6ributes

Inbound
(control)
interface

↔

Opera9ons

Black
Box

↔

Object

Trajectory

↔

Path
in
Statechart

Encapsula9on

↔

Encapsula9on

Abstrac9on

↔

Abstrac9on

Hierarchic
architecture

↔

Hierarchic
architecture

Transforma9on

↔

Object
behaviour

Per Olof Arnäs,

57
Image: Connected. 362/365 by AndYaDontStop on Flickr.com

Advantages
of
using
object-‐orienta9on

Analysis

Consistent
framework

Sta9c
structure
Dynamic
behaviour
Sequences
Use
cases
Etc.

Per Olof Arnäs,

Visualisa9on

Design
Object-‐oriented

analysis
facilitates

future
(re-‐)design

58

Three
approaches

123
Per Olof Arnäs,

59

Long-‐term
control
scope
Time-‐span:
Years
to
months

1

Driving
ques9ons:

What
states
should
the

system
be
able
to
assume?
What
component
types
are

required
for
the
system
to

Important
tasks:
assume
these
states?

Define
the
data-‐structure
of
the
top-‐
level
classes
of
the
system,
i.e.
the

interface
widths.
Define
acceptable
data
ranges
for
these

classes,
i.e.
the
interface
depths.
Descrip9ve
complexity
is
reduced

Define
acceptable
use
cases.

by
robust
design

Per Olof Arnäs,

60

Medium-‐term
control
scope
Time-‐span:
Months
to
weeks

2

Driving
ques9ons:

Important
tasks:

What
components
are

needed
in
the
system?
How
are
the
various

interfaces
designed?

Deﬁne
actual
use
cases.
Deﬁne
interface
width
of
all
classes.
Apply
constraints
to
reduce
interface

depth.

Per Olof Arnäs,

Computa9onal
complexity
is

reduced
by
good
planning

61

3

Short-‐term
(real9me)
control
scope
Time-‐span:
Weeks
to
minutes

Driving
ques9on:

What
state
changes
should

be
performed
and
how?

Important
tasks:
Control
the
actual
trajectory
as
it

progresses
through
the
state
space.

Uncertainty-‐based
complexity
is

reduced
by
crea9ng
order

Per Olof Arnäs,

62

Examples
Focusing
on
interfaces

Per Olof Arnäs,

HETEROGENEOUS GOODS

Per Olof Arnäs,

Arnäs, Woxenius – Approach for handling heterogeneous goods in
intermodal freight networks – revisited, WCTR 2013

Heterogeneous goods leads
to increased complexity

Per Olof Arnäs,

Image: http://sobar.soso.com/t/74147926?fl=29

Heterogeneous goods leads
to increased complexity

Density

Per Olof Arnäs,

Handling

Image: http://sobar.soso.com/t/74147926?fl=29

Stowability

Liability

What
makes
some
goods
heterogeneous? 
Four
dimensions:

Low/high
density

Diﬃculty
of
handling
Per Olof Arnäs,

Poor
stowability

Extended
liability
67

Deep
fryers

ProducWon/Factories
Wholesaler,

”Supply
chain
manager”

Fries

Customer
Order
Point/Warehouse

CC-‐BY
Per
Olof
Arnäs,
LogisWkfokus

Resellers

Market
place

Customers
CC-BY Dr Logistics – Per Olof
Arnäs

Short
reading
list
•

Klir,
G.
J.
(1991)
Facets
of
systems
science,
Plenum
Press,
New
York. 

•

Booch,
G.
(1991)
Object
oriented
design
with
applica9ons,
Benjamin/Cummings

Pub.
Co.,
Redwood
City,
Calif. 

•

Ashby,
W.
R.
(1956)
An
introduc9on
to
Cyberne9cs,
Chapman
&
Hall
Ltd,

London. 

•

Beer,
S.
(1959)
Cyberne9cs
and
management,
English
UniversiWes
Press
ltd,

London. 

•

CasW,
J.
L.
(1989)
Alternate
reali9es
:
mathema9cal
models
of
nature
and
man,

Wiley,
New
York
;
Chichester. 

Per Olof Arnäs,

70

PhD-‐theses
•

Hultén,
L.
A.
R.
(1997)
Container
logisWcs
and
its
management,
Department
of
Transporta9on
and

Logis9cs,
Chalmers
University
of
Technology,
Göteborg 

•

Franzén,
S.
E.
R.
(1999)
Public
transporta9on
in
a
systems
perspec9ve
:
a
conceptual
model
and
an

analy9cal
framework
for
design
and
evalua9on,
Chalmers
tekniska
högsk.,
Göteborg. 

•

Waidringer,
J.
(2001)
Complexity
in
transporta9on
and
logis9cs
systems
:
an
integrated
approach
to

modelling
and
analysis,
Chalmers
tekniska
högsk.,
Göteborg. 

•

Nilsson,
F.
(2005)
AdapWve
LogisWcs
-‐
using
complexity
theory
to
facilitate
increased
eﬀecWveness
in

logisWcs,
Department
of
Design
Sciences,
Lund
University,
Lund,
Sweden 

•

Arnäs,
P.
O.
(2007)
Heterogeneous
Goods
in
TransportaWon
Systems
-‐
A
study
on
the
uses
of
an

object-‐oriented
approach,
Doktorsavhandlingar
vid
Chalmers
tekniska
högskola.
Ny
serie,
2625,

Chalmers
University
of
Technology,
Göteborg

Per Olof Arnäs,

71

And
ﬁnally…

The Internet first became available for
Swedish consumers around 1993

+

=
A (bad and expensive) mix between Teletext
and the Yellow Pages

Not very pretty

Few people with computers
Per Olof Arnäs,

15 years later, in 2008, Google Flu
Trends was launched
Based on what
people google and
where their
computer is located

www.google.org
Ten days ahead
of the official flu
tracker
Per Olof Arnäs,

How
will
we
use
the
technology
in
10
years?
os t
alm

We have no idea.
!

...and neither does she,
but she will be dissatisfied
with stuff that we think are
pure science fiction and
almost magic.

Per Olof Arnäs,

The girl and the iPad by Niclas Lindh on Flickr (CC-BY)

How
will
we
use
the
technology
in
10
years?

Thank
you!

!

Per
Olof
Arnäs
per-‐olof.arnas@chalmers.se
@Dr_PO

Per Olof Arnäs,

The girl and the iPad by Niclas Lindh on Flickr (CC-BY)

Complexity - Controlling chaos using cybernetics and good design

Recommended

Recommended

More Related Content

Similar to Complexity - Controlling chaos using cybernetics and good design

Similar to Complexity - Controlling chaos using cybernetics and good design (20)

More from Per Olof Arnäs

More from Per Olof Arnäs (20)

Recently uploaded

Recently uploaded (20)

Complexity - Controlling chaos using cybernetics and good design