Complexity
Controlling	
  chaos	
  using	
  cyberne5cs	
  and	
  
good	
  design	
  
P.O.	
  Arnäs,	
  PhD	
  
Per-­‐Olof....
What	
  is	
  a	
  
system?
Per Olof Arnäs,
Technology Management and Economics,
Division of Logistics and Transportation
...
A	
   set	
   consists	
   of	
  
more	
   than	
   one	
  
elementary	
  part

Per Olof Arnäs,
Technology Management and ...
A	
   set	
   consists	
   of	
  
more	
   than	
   one	
  
elementary	
  part

A	
  system	
  differs	
  from	
  
a	
  set...
A	
   set	
   consists	
   of	
  
more	
   than	
   one	
  
elementary	
  part

The	
  whole	
  shows	
  
proper5es	
  tha...
A	
   set	
   consists	
   of	
  
more	
   than	
   one	
  
elementary	
  part

A	
  system	
  cannot	
  be	
  
fully	
  u...
A	
   set	
   consists	
   of	
  
more	
   than	
   one	
  
elementary	
  part

A	
  system	
  cannot	
  be	
  
fully	
  u...
Gödel´s	
  incompleteness	
  theorem

A	
  system	
  cannot	
  be	
  fully	
  defined	
  from	
  within
Per Olof Arnäs,
Tec...
Gödel´s	
  incompleteness	
  theorem
I	
  don´t	
  
understand

I	
  don´t	
  
understand

Neither	
  do	
  I

A	
  system...
I	
  don´t	
  
understand

Neither	
  do	
  I

Per Olof Arnäs,
Technology Management and Economics,
Division of Logistics ...
Important	
  terms

”State”	
  –	
  The	
  current	
  
value	
  of	
  the	
  a6ributes

Si = (xi, yi, zi, vi)

”A6ributes”...
:

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
...
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
Disturbanc...
The main task

Handle complexity
Per Olof Arnäs,
Technology Management and Economics,
Division we did at work today (Rawwr...
Complexity – 3 types

Each type is associated with a specific
complexity driver
Complexity driver: A variable that indicat...
1.	
  Descrip9ve	
  complexity
Difficulty	
  in	
  describing	
  
the	
  system
”Variety”	
  =	
  The	
  total	
  number	
  ...
1.	
  Descrip9ve	
  complexity
Road	
  terminal,
local

Consignor

DomesWc	
  
rail	
  terminal
Per Olof Arnäs,
Technology...
1.	
  Descrip9ve	
  complexity
Road	
  terminal,
local

ed
s

e

tiv
p

ri
c

s

de

e

pl

Road	
  terminal,
central

om
...
2.	
  Computa9onal	
  complexity
Difficulty	
  in	
  finding	
  the	
  
”best”	
  trajectory	
  through	
  
the	
  state	
  s...
2.	
  Computa9onal	
  complexity
Road	
  terminal,
central
Road	
  terminal,
local

Consignor

?

DomesWc	
  
rail	
  term...
2.	
  Computa9onal	
  complexity
Road	
  terminal,
central
Road	
  terminal,
local

Consignor

?

Road	
  terminal,
local
...
3.	
  Uncertainty-­‐based	
  complexity
Difficulty	
  in	
  describing	
  the	
  
state	
  of	
  the	
  system

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

Consignor

✓

DomesWc	
  
rail	...
3.	
  Uncerta9nty-­‐based	
  complexity

Road	
  terminal,
local

Consignor

✓

Road	
  terminal,
central

?

✓

?

?
Dome...
Cyberne9cs

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

?

25
Cyberne9cs

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

26
Cyberne9cs
Output
In

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

In

I...
Cyberne9cs
Launched	
  as	
  a	
  branch	
  of	
  
systems	
  science	
  in	
  the	
  
1940´s
W
g

f
X

Mathema9cs	
  as	
...
Processes	
  on	
  various	
  levels	
  (redrawn	
  from	
  NEVEM,	
  1989).	
  

Per Olof Arnäs,
Technology Management an...
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
Disturbanc...
Organize	
  the	
  trains	
  
into	
  groups.	
  How	
  
can	
  they	
  be	
  
grouped?	
  
Discuss	
  in	
  small	
  
gro...
2-­‐4	
  wagons
7	
  types	
  of	
  cargo
2	
  types	
  of	
  wheels
2	
  wagon	
  sizes
4	
  wagon	
  types
4	
  wagon	
 ...
GOAL:

	
  

Pizza Menu

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

33
Per Olof Arnäs,
Technology Management and Economics,
Division of Logistics and Transportation

34
Per Olof Arnäs,
Technology Management and Economics,
Division of Logistics and Transportation

35
Interface	
  design
In	
  order	
  to	
  handle	
  the	
  three	
  complexity	
  types,	
  a	
  
modelling/design	
  proce...
An interface is a representation
of a system displaying its visible
state and its visible inputs.

The System

Visible

at...
Dimension	
  1:	
  Interface	
  direcWon

Inbound interface

Per Olof Arnäs,
Technology Management and Economics,
Division...
Dimension	
  2:	
  Interface	
  width
The width of the interface
consists of the number of
attributes/operations

h

idt

...
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...
Dimension	
  3:	
  Interface	
  depth
The variety of each attribute and
operation together constitute the
interface depth
...
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
...
NARROW

Few parameters

SHALLOW
Binary
parameters

Degenerated
encapsulation

Interface
WIDTH

WIDE

Many parameters
Encap...
Reducing	
  complexity	
  –	
  some	
  ground	
  rules
Exclude	
  variables
Diminish	
  state	
  space
Par99on	
  states
G...
Key	
  tools	
  in	
  cyberne9cs
Black	
  boxes
In

In

In

In

Encapsulate	
  func9on
Encapsulate	
  content

In

Hierarc...
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
...
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...
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...
How	
  would	
  a	
  
programmer	
  
design	
  a	
  complex	
  
system?
Per Olof Arnäs,
Technology Management and Economic...
A	
  parallel	
  history
In	
  1967,	
  the	
  programming	
  
language	
  Simula	
  67	
  was	
  launched
!
The	
  first	
...
The	
  canonical	
  form	
  of	
  a	
  complex	
  system	
  (redrawn	
  from	
  Booch,	
  1991).
Per Olof Arnäs,
Technolog...
Class	
  diagrams
1

Consignment
1..4

1
*

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

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

The topmost cell contains...
The class Box.

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

54
An object of the class Pallet can contain several objects of the class Box. The denotations 1 and * means that
one pallet ...
Object-­‐orienta9on	
  is	
  applied	
  cyberne9cs!
When	
  looking	
  at	
  the	
  core	
  concepts	
  of	
  object-­‐
or...
Systems	
  theory

Object-­‐orienta9on

System	
  model

↔

Object	
  model

State

↔

State

Outbound	
  (display)	
  int...
Advantages	
  of	
  using	
  object-­‐orienta9on

Analysis

Consistent	
  framework

Sta9c	
  structure
Dynamic	
  behavio...
Three	
  approaches

123
Per Olof Arnäs,
Technology Management and Economics,
Division of Logistics and Transportation

59
Long-­‐term	
  control	
  scope
Time-­‐span:	
  Years	
  to	
  months

1

Driving	
  ques9ons:

What	
  states	
  should	
...
Medium-­‐term	
  control	
  scope
Time-­‐span:	
  Months	
  to	
  weeks

2

Driving	
  ques9ons:

Important	
  tasks:

Wha...
3

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

Driving	
  ques9on:

What	
  stat...
Examples
Focusing	
  on	
  interfaces

Per Olof Arnäs,
Technology Management and Economics,
Division of Logistics and Tran...
HETEROGENEOUS GOODS

Per Olof Arnäs,
Technology Management and Economics,
Division of Logistics and Transportation
Arnäs, Woxenius – Approach for handling heterogeneous goods in
intermodal freight networks – revisited, WCTR 2013

Heterog...
Heterogeneous goods leads
to increased complexity

Density

Per Olof Arnäs,
Technology Management and Economics,
Division ...
What	
  makes	
  some	
  goods	
  heterogeneous?

Four	
  dimensions:

Low/high	
  density

Difficulty	
  of	
  handling
Per...
Deep	
  fryers

ProducWon/Factories
Wholesaler,	
  
”Supply	
  chain	
  manager”

Fries

Customer	
  Order	
  Point/Wareho...
Deep	
  fryers

ProducWon/Factories
Wholesaler,	
  
”Supply	
  chain	
  manager”

Fries

Customer	
  Order	
  Point/Wareho...
Short	
  reading	
  list
•

Klir,	
  G.	
  J.	
  (1991)	
  Facets	
  of	
  systems	
  science,	
  Plenum	
  Press,	
  New	...
PhD-­‐theses
•

Hultén,	
  L.	
  A.	
  R.	
  (1997)	
  Container	
  logisWcs	
  and	
  its	
  management,	
  Department	
 ...
And	
  finally…	
  

The Internet first became available for
Swedish consumers around 1993

+

=
A (bad and expensive) mix ...
15 years later, in 2008, Google Flu
Trends was launched
Based on what
people google and
where their
computer is located

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

We have no idea.
!

...and neither does she,...
How	
  will	
  we	
  use	
  the	
  technology	
  in	
  10	
  years?

Thank	
  you!	
  
!

	
  

Per	
  Olof	
  Arnäs
per-­...
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Complexity - Controlling chaos using cybernetics and good design

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What is a complex system? How can it be controlled? What is cybernetics and why is it so cool?

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Complexity - Controlling chaos using cybernetics and good design

  1. 1. 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)
  2. 2. What  is  a   system? Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 2
  3. 3. A   set   consists   of   more   than   one   elementary  part Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 3
  4. 4. A   set   consists   of   more   than   one   elementary  part A  system  differs  from   a  set  when  it  displays   emergent  proper,es Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 4
  5. 5. 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, Technology Management and Economics, Division of Logistics and Transportation 5
  6. 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, Technology Management and Economics, Division of Logistics and Transportation 6
  7. 7. 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, Technology Management and Economics, Division of Logistics and Transportation 7
  8. 8. Gödel´s  incompleteness  theorem A  system  cannot  be  fully  defined  from  within Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 8
  9. 9. 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, Technology Management and Economics, Division of Logistics and Transportation 9
  10. 10. I  don´t   understand Neither  do  I Per Olof Arnäs, Technology Management and Economics, Division of Logistics and  Transportation 2009  -­‐  October  -­‐ NodeXL  Facebook  Network  Marc  Smith  FR  Layout  by  Marc_Smith  on  flickr.com I  don´t   understand
  11. 11. 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, Technology Management and Economics, Division of Logistics and Transportation ”Trajectory”  –  a   succession  of  states Image:  Bouncing  ball  strobe  edit,  CC-­‐BY    Richard  Bartz,  Wikimedia  Commons 11
  12. 12. :
 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, Technology Management and Economics, Division of Logistics and Transportation controlled! Conceptual  model  of  a  transportaWon  process  as  a   trajectory  between  states  (adopted  from  Hultén,  1997).   12
  13. 13. 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, Technology Management and Economics, Division of Logistics and Transportation 13
  14. 14. The main task Handle complexity Per Olof Arnäs, Technology Management and Economics, Division we did at work today (Rawwrrrr!) What of Logistics and Transportation by Amit Gupta on Flickr (CC BY-NC)
  15. 15. 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, Technology Management and Economics, Division we did at work today (Rawwrrrr!) What of Logistics and Transportation by Amit Gupta on Flickr (CC BY-NC)
  16. 16. 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, Technology Management and Economics, Division of Logistics and Transportation Image:  ”Jan  2005  Map  of  the  Internet”  BY  ma_hewje_hall   on  flickr 16
  17. 17. 1.  Descrip9ve  complexity Road  terminal, local Consignor DomesWc   rail  terminal Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation DomesWc port Foreign port Consignee Foreign   rail  terminal 17
  18. 18. 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, Technology Management and Economics, Division of Logistics and Transportation DomesWc In port Foreign port Consignee Foreign   rail  terminal 18
  19. 19. 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, Technology Management and Economics, Division of Logistics and Transportation b)  which  of  the  possible   trajectories  should  be  chosen Image:  ”Playing  chess”  BY  Jeffrey  Barke  on  flickr 19
  20. 20. 2.  Computa9onal  complexity Road  terminal, central Road  terminal, local Consignor ? DomesWc   rail  terminal Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation Road  terminal, local ? DomesWc port Foreign port Consignee Foreign   rail  terminal 20
  21. 21. 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, Technology Management and Economics, Division of Logistics and Transportation Consignee Foreign   rail  terminal 21
  22. 22. 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, Technology Management and Economics, Division of Logistics and Transportation Image:  ”Jam  at  the  floaWng  market”   BY  Stuck  in  Customs  on  flickr 22
  23. 23. 3.  Uncerta9nty-­‐based  complexity Road  terminal, central Road  terminal, local Consignor ✓ DomesWc   rail  terminal Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation ✓ ✓ DomesWc port ✓ Foreign port Road  terminal, local ✓ ✓ ✓ Consignee Foreign   rail  terminal 23
  24. 24. 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, Technology Management and Economics, Division of Logistics and Transportation ? Foreign   rail  terminal 24
  25. 25. Cyberne9cs Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation ? 25
  26. 26. Cyberne9cs Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 26
  27. 27. Cyberne9cs Output In Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation In In In In 27
  28. 28. 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, Technology Management and Economics, Division of Logistics and Transportation Image:  ”Wheldrake  sundial”  BY  Darwin70  on  flickr 28
  29. 29. Processes  on  various  levels  (redrawn  from  NEVEM,  1989).   Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 29
  30. 30. 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, Technology Management and Economics, Division of Logistics and Transportation 30
  31. 31. 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, Technology Management and Economics, Division of Logistics and Transportation 31
  32. 32. 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, Technology Management and Economics, Division of Logistics and Transportation 32
  33. 33. GOAL:   Pizza Menu Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 33
  34. 34. Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 34
  35. 35. Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 35
  36. 36. 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, Technology Management and Economics, Division of Logistics and Transportation Image:  ”MacBook  Air  by  Jony  Ive”  BY   36 marcopako    on  flickr
  37. 37. 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, Technology Management and Economics, Division of Logistics and Transportation 37
  38. 38. Dimension  1:  Interface  direcWon Inbound interface Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 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
  39. 39. 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, Technology Management and Economics, Division of Logistics and Transportation Image:  ”MacBook  Air  by  Jony  Ive”  BY   39 marcopako    on  flickr
  40. 40. 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, Technology Management and Economics, Division of Logistics and Transportation Image:  ”MacBook  Air  by  Jony  Ive”  BY   40 marcopako    on  flickr
  41. 41. 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, Technology Management and Economics, Division of Logistics and Transportation Image:  ”MacBook  Air  by  Jony  Ive”  BY   41 marcopako    on  flickr
  42. 42. 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, Technology Management and Economics, Division of Logistics and Transportation Image:  ”MacBook  Air  by  Jony  Ive”  BY   42 marcopako    on  flickr
  43. 43. 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, Technology Management and Economics, Division of Logistics and Transportation Constraints make interfaces more shallow No encapsulation – open system 43
  44. 44. 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, Technology Management and Economics, Division of Logistics and Transportation 44
  45. 45. 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, Technology Management and Economics, Division of Logistics and Transportation 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
  46. 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 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, Technology Management and Economics, Division of Logistics and Transportation 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
  47. 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   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, Technology Management and Economics, Division of Logistics and Transportation 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
  48. 48. 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, Technology Management and Economics, Division of Logistics and Transportation 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
  49. 49. How  would  a   programmer   design  a  complex   system? Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation
  50. 50. 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, Technology Management and Economics, Division of Logistics and Transportation 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
  51. 51. The  canonical  form  of  a  complex  system  (redrawn  from  Booch,  1991). Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 51
  52. 52. 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, Technology Management and Economics, Division of Logistics and Transportation 1 * DGD item Size 1 Waybill -Statement -Name -Signature Length Number of pallets Volume 52
  53. 53. 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, Technology Management and Economics, Division of Logistics and Transportation 53
  54. 54. The class Box. Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 54
  55. 55. 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, Technology Management and Economics, Division of Logistics and Transportation 55
  56. 56. 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, Technology Management and Economics, Division of Logistics and Transportation 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
  57. 57. 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, Technology Management and Economics, Division of Logistics and Transportation 57 Image: Connected. 362/365 by AndYaDontStop on Flickr.com
  58. 58. Advantages  of  using  object-­‐orienta9on Analysis Consistent  framework Sta9c  structure Dynamic  behaviour Sequences Use  cases Etc. Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation Visualisa9on Design Object-­‐oriented   analysis  facilitates   future  (re-­‐)design 58
  59. 59. Three  approaches 123 Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation 59
  60. 60. 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, Technology Management and Economics, Division of Logistics and Transportation 60
  61. 61. 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, Technology Management and Economics, Division of Logistics and Transportation Computa9onal  complexity  is   reduced  by  good  planning   61
  62. 62. 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, Technology Management and Economics, Division of Logistics and Transportation 62
  63. 63. Examples Focusing  on  interfaces Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation
  64. 64. HETEROGENEOUS GOODS Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation
  65. 65. Arnäs, Woxenius – Approach for handling heterogeneous goods in intermodal freight networks – revisited, WCTR 2013 Heterogeneous goods leads to increased complexity Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation Image: http://sobar.soso.com/t/74147926?fl=29
  66. 66. Heterogeneous goods leads to increased complexity Density Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation Handling Image: http://sobar.soso.com/t/74147926?fl=29 Stowability Liability
  67. 67. What  makes  some  goods  heterogeneous?
 Four  dimensions: Low/high  density Difficulty  of  handling Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation Poor  stowability Extended  liability 67
  68. 68. 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  
  69. 69. 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  
  70. 70. 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, Technology Management and Economics, Division of Logistics and Transportation 70
  71. 71. 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, Technology Management and Economics, Division of Logistics and Transportation 71
  72. 72. 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, Technology Management and Economics, Division of Logistics and Transportation
  73. 73. 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, Technology Management and Economics, Division of Logistics and Transportation
  74. 74. 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, Technology Management and Economics, Division of Logistics and Transportation The girl and the iPad by Niclas Lindh on Flickr (CC-BY)
  75. 75. How  will  we  use  the  technology  in  10  years? Thank  you!   !   Per  Olof  Arnäs per-­‐olof.arnas@chalmers.se @Dr_PO Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation The girl and the iPad by Niclas Lindh on Flickr (CC-BY)  

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