complexity - controlling chaos using cybernetics and good design

Per Olof Arnäs, Technology Management and Economics, Division of Logistics and TransportationWhat we did at work today (Rawwrrrr!) by Amit Gupta on Flickr (CC BY-NC)

ComplexityControlling chaos using cyberne5cs and

good design P.O. Arnäs, PhD

Per-‐[email protected] @Dr_PO

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

What is a system?

�2


A set consists of more than one elementary part

�3


A system differs from a set when it displays emergent proper,es


�4


The whole shows proper5es that are not

found in its parts



�5

Reduc5onism is not applicable




A system cannot be fully understood by studying its parts

separately


found in its parts


�6




A system cannot be fully understood by studying its parts

separately


found in its parts

�7



A system cannot be fully defined from within

Gödel´s incompleteness theorem

�8


A system cannot be fully defined from whithin

Gödel´s incompleteness theorem

I don´t understand

I don´t understand

Neither do I

�9

Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation2009 -‐ October -‐ NodeXL Facebook Network Marc Smith FR Layout by Marc_Smith on flickr.com

I don´t understand

I don´t understand

Neither do I


Si = (xi, yi, zi, vi)

”Trajectory” – a succession of states

”State” – The current value of the a6ributes

”A6ributes” – a collec9on of the system’s variables

(degrees of freedom):

e.g. X, Y, Z, V

Important terms

Image: Bouncing ball strobe edit, CC-‐BY Richard Bartz, Wikimedia Commons �11


Transportation system

State space, S

Resources, R

Goods in initial state,

S0

Goods in goal state, S1

Trajectory = f(S0, S1, R)

Conceptual model of a transportaWon process as a trajectory between states (adopted from Hultén, 1997).

This process needs to be

controlled!

The system

s perspec

tive:

The transpo

rtation

process

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

Goa

l state

Syst

em s

tate,

output

Input

Feedback loop

Disturbance

Regulated system !

(transportation system)

Regulator !

(TCS)

COMPLE

XITY!!

!

COMPLEXITY!!!

COMPLEXITY!!!

COMPLEXITY!!!

�13


The main task

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

Handle complexity


Complexity – 3 types

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

Each type is associated with a specific complexity driver

Complexity driver: A variable that indicates increase/decrease in complexity


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

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

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Consignor Consignee

DomesWc port

Foreign port

Road terminal, local

DomesWc rail terminal

Foreign rail terminal

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Consignor Consignee

DomesWc port

Foreign port




Road terminal, central


�18

Incre

ased d

escrip

tive co

mplexit

y

Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation Image: ”Playing chess” BY Jeffrey Barke on flickr

2. Computa9onal complexityDifficulty in finding the

”best” trajectory through the state space

The controller needs to know:

b) which of the possible trajectories should be chosen

a) which of the states are valid

Complexity driver: The number and length of

valid trajectories�19


Consignor Consignee

DomesWc port

Foreign port






2. Computa9onal complexity

?

?

�20


Consignor Consignee

DomesWc port

Foreign port






2. Computa9onal complexity

?

?

?

?

?Increa

sed computation

al complexit

y

�21


Image: ”Jam at the floaWng market” BY Stuck in Customs on flickr

3. Uncertainty-‐based complexityDifficulty in describing the

state of the system

Complexity driver: The number of decisions that must be made during the transporta9on process

The amount of informa9on needed to describe the state of the system

Measured by the informa,on entropy

Controller needs to ”step into” the system during the preocess to resolve uncertainty

�22


Consignor Consignee

DomesWc port

Foreign port






3. Uncerta9nty-‐based complexity

✓✓

✓

✓

✓

✓

✓

�23


Consignor Consignee

DomesWc port

Foreign port






3. Uncerta9nty-‐based complexity

?

Increased uncertainty-based complexity

✓

✓

?

?

?

?

�24

??


Cyberne9cs

�25

?


Cyberne9cs

�26


Cyberne9cs

OutputIn In In In In

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Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation Image: ”Wheldrake sundial” BY Darwin70 on flickr

Cyberne9csLaunched as a branch of systems science in the

1940´s Mathema9cs as a modelling language

W G

Xg h

f

CasW's model of the input/output relaWon (redrawn from CasW, 1989, p. 109)

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

�29


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

Goa

l state

Syst

em s

tate,

output

Input

Feedback loop

Disturbance

Regulated system !

(transportation system)

Regulator !

(TCS)

COMPLE

XITY!!

!

COMPLEXITY!!!

COMPLEXITY!!!

COMPLEXITY!!!

�30


Organize the trains into groups. How can they be grouped?

Discuss in small groups and try to find the most logical solu9on.

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Bild: Booch, 1991


Bild: Booch, 1991

2-‐4 wagons

7 types of cargo

2 types of wheels

2 wagon sizes

4 wagon types

4 wagon roofs

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GOAL:

Pizza Menu

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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


Image: ”MacBook Air by Jony Ive” BY marcopako on flickr

Interface designIn 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

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The System

Visibleattributes

Sta

te

Visibleinputs

Interface

Inbound interface Outbound interfaceThe interface hides (encapsulates)

content and function

An interface is a representation of a system displaying its visible

state and its visible inputs.

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The System

Visibleattributes

Sta

te vec

torVisible

inputs

Inbound interface Outbound interface

Dimension 1: Interface direcWon

An interface can be either inbound or outbound

Ope

ration

s vect

or

�38



Dimension 2: Interface width

The width of the interface consists of the number of

attributes/operations

The SystemWidthWidth

More attributes (degrees of freeedom) – wider interface

More operations – wider interface

The interface width is reduced by

encapsulation

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EncapsulaWon

The System

The System

Encaps

ulatio

n

of co

ntent

Encapsu

lation

of functi

on

Hidden attributes

Hidden inputs

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Dimension 3: Interface depthThe variety of each attribute and operation together constitute the

interface depth

The System

Depth DepthThe interface depth

is reduced by applying constraints

The depth can range from binary to continuous

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Constraints

The System

The System

Stati

onary

conts

traint

s

Transitor

y

constrain

ts

Limiting states

Limiting operations

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Interface WIDTH

Int

erfa

ce

DEP

TH

NARROW WIDE

SHALLOW

DEEP

Many parametersFew parameters

Binary parameters

Discreet parameters

Continous Parameters

with constraints

Continous Parameters

Constraints make interfaces more shallow

Encapsulation limits interface widthDegenerated

encapsulation

No encapsulation – open system

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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 Create mul9ple levels of abstrac9on

Image: ”Jam at the floaWng market” BY Stuck in Customs on flickrImage: ”Playing chess” BY Jeffrey Barke on flickrImage: ”Jan 2005 Map of the Internet” BY ma_hewje_hall on flickr

�44


Key tools in cyberne9cs

In In In In In

Feedback loop

Syst

em s

tate,

output

Input

Disturbance

Regulated system !(transportation

system)

Regulator !(TCS)

Black boxes Encapsulate func9on Encapsulate content

Hierarchic system models

Control Theory Regulator Trajectory which needs to be controlled Finite state space

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In

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By construc9ng the system from a number of black boxes, complexity can be reduced

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In

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By construc9ng the system from a number of classes, complexity can be reduced

�48


How would a programmer

design a complex system?

Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation Image: ”Wheldrake sundial” BY Darwin70 on flickr

A parallel historyIn 1967, the programming

language Simula 67 was launched !

The first object-‐oriented language !

Used to build discrete event simula9on models

“…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)

Discrete event simula9on

Si = (xi, yi, zi, vi)

Remember

TRAJECTORY

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

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Class diagrams

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Consignment

11..4

Waybill

Waybill item

1*

Physical

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

DG fact sheet-Statement-Name-Signature

Sender certificate Dangerous Goods Declaration

-Product name-UN number-Quantity-Packing

DGD item

1

*

Consignment documentation

Electronic

-Consignor-Consignee-Customer number

Order

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

Order Item

Weight VolumeLength Number of pallets

Size

1

*

1

*

1 *

1

*

Product

1

*

+Overpack()+Open()+Move()+Fill()+Empty()

-Weight-Size-Position

Pallet


+MoveTo(in NewX, in NewY, in NewZ)+LiftUp(in Distance)+PutDown()

Pallet-Height-Width-Depth-Weight-Pos-X-Pos-Y-Pos-Z

A class is a template for real-world objects

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

The topmost cell contains the name

The middle cell contains the attributes

The bottom cell contains the operations

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The class Box.

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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.

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Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation Image: Connected. 362/365 by AndYaDontStop on Flickr.com

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?

Different disciplines (Systems science/Mathema9cs vs Computer science) Some advances have been made towards a combina9on, but these are few

�56

Per Olof Arnäs, Technology Management and Economics, Division of Logistics and Transportation Image: Connected. 362/365 by AndYaDontStop on Flickr.com

Systems theory Object-‐orienta9onSystem 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

�57


Advantages of using object-‐orienta9on

Visualisa9on

Consistent framework Sta9c structure

Dynamic behaviour Sequences Use cases

Etc.

Design

Analysis

Object-‐oriented analysis facilitates future (re-‐)design

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Three approaches

123�59


Long-‐term control scope 1Time-‐span: Years to months

Important tasks: 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. Define acceptable use cases. Descrip9ve complexity is reduced

by robust design

Driving ques9ons: What states should the

system be able to assume? What component types are required for the system to

assume these states?

�60


Medium-‐term control scope 2Time-‐span: Months to weeks

Driving ques9ons: What components are needed in the system? How are the various interfaces designed?

Important tasks: Define actual use cases. Define interface width of all classes. Apply constraints to reduce interface depth.

Computa9onal complexity is reduced by good planning

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Short-‐term (real9me) control scope3Time-‐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

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Examples

Focusing on interfaces


HETEROGENEOUS GOODS


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

Heterogeneous goods leads to increased complexity

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


Heterogeneous goods leads to increased complexity

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

Density Handling Stowability Liability


What makes some goods heterogeneous? Four dimensions:

Difficulty of handling

Poor stowability

Extended liability

Low/high density

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CC-‐BY Per Olof Arnäs, LogisWkfokus

Market place

Customer Order Point/Warehouse

Resellers

Customers

ProducWon/FactoriesWholesaler, ”Supply chain manager”

Fries

Deep

fryers

CC-BY Dr Logistics – Per Olof Arnäs

drlogistics.se - @DrLogistics


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.

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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

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+ =

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

And finally…


15 years later, in 2008, Google Flu Trends was launched

Based on what people google and where their computer is located

Ten days ahead of the official flu

tracker

www.google.org


How will we use the technology in 10 years?

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.

almost

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


How will we use the technology in 10 years?

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

Thank you! !

Per Olof Arnäs per-‐[email protected]

@Dr_PO