simulation - SOLE® - Scandinavian Organisation of Logistics

Scandinavian Organisation of Logistics Engineers

(SOLE)

OPTIMISE - A web-services based platform for simulation-based optimisation:

applications in production and logistics

Amos H.C. Ng (PhD, MIET)

Senior Lecturer

Centre for Intelligent Automation

University of Skövde,

PO Box 408, 54128 Skövde, Sweden

amos.ng@his.se

A KKS HÖG 2004 project1 April 2005 – 31 March 2008

OPTIMisation: using Intelligent Simulation Tools

(OPTIMIST)

Amos Ng

Centre for Intelligent Automation

Our research areas:� Manufacturing machinery/machinesystems simulation

� Integrated product and process development through VirtualManufacturing and Digital Plants

� Simulation support for health caresystem design and planning

� Simulation-basedscheduling/optimisation

Scandinavian Organisation of Logistics Engineers

(SOLE)

1. What is simulation-based optimisation and why

2. Why OPTIMISE: an industrial perspective

3. Why OPTIMISE: a research perspective

4. Overview of some industrial test cases

5. The PRiTSi test case with Posten

Presentation Agenda :

Scandinavian Organisation of Logistics Engineers

(SOLE)

1. What is simulation-based optimisation and why

2. Why OPTIMISE: an industrial perspective

3. Why OPTIMISE: a research perspective

4. Overview of some industrial test cases

5. The PRiTSi test case with Posten

Presentation Agenda :

Amos Ng

Simulation is Not the Goal

Cogito ergo sum! (I think, therefore I am!)

René Descartes

I simulate, therefore I optimise!

A simulation engineer

Perfection of means and confusion of goals seem to characterize our age.

Albert Einstein

Amos Ng

Simulation ≠≠≠≠Optimisation

”Optimal”solution

ObjectiveGenerative

Model(AI)

e.g. Expert system,mathematical programming

e.g. utilisation e.g. no. of machines

EvaluativeModel

(Simulation)

e.g. Simulation,queueing networks

DesignPerformance

measures

e.g. no. of machines e.g. utilisation

Do you know that simulation is not an optimisation tool?

Are there any “real” optimisation tools?

Problems must be abstracted and formulated formally based on unrealistic assumptions.

Amos Ng

Simulation-based Optimisation

Requirements:

� Validated simulation models

� On-line system data for operational optimisation

� Intelligent optimisation engine

� Much much computing power/time …

EvaluativeModel

(Simulation)

GenerativeModel

(AI)

Evaluative data

Control parameters

Amos Ng

The Future of Simulation

One of the disadvantages of simulation historically is that it was not an optimisation technique…simulation-based optimisation is the most important new simulation technology in the last five years

…it is relatively new, but it will have a considerable impact on the practice of simulation in the future, particularly when computers become significantly faster.

Averill Law2002 WSC

(Author of the book: Simulation modelling and analysis)

Scandinavian Organisation of Logistics Engineers

(SOLE)

1. What is simulation-based optimisation and why

2. Why OPTIMISE: an industrial perspective

3. Why OPTIMISE: a research perspective

4. Overview of some industrial test cases

5. The PRiTSi test case with Posten

Presentation Agenda :

Amos Ng

Project Aim

To leverage the effectiveness of the Swedish

industrial and logistic sectors by introducing

Simulation-Based Optimisation (SBO) to their

system design and daily operations.

Amos Ng

OPTIMIST: Objectives

Objectives:

� Real-life industrial and logistic test cases.

� Gain and then spread the knowledge and experience of applying SBO and advanced simulation techniques in Sweden.

� OPTIMISE (OPTIMsation with Intelligent Simulation and Experimentation) -

a software environment that tightly integrates Discrete-Event Simulation (DES) systems, soft-computing optimisation tools, realised on a Web-Services platform.

Amos Ng

OPTIMISE

Optimal or sub-optimal solutionData Analysis

Realisation of a Web-services based simulation platform

Amos Ng

http://Optimise.its.his.se/optimise/service.asmx

Scandinavian Organisation of Logistics Engineers

(SOLE)

1. What is simulation-based optimisation and why

2. Why OPTIMISE: an industrial perspective

3. Why OPTIMISE: a research perspective

4. Overview of some industrial test cases

5. The PRiTSi test case with Posten

Presentation Agenda :

Amos Ng

Some of Our Research Focuses

� Advanced search algorithms and methods that are, e.g. applicable for stochastic simulation (noisy optimisation), multi-objective, and/or moreefficient for specific complex real-world productionand logistic applications. � Methods to handle imprecision/errors from the

metamodels/surrogate models in SBO processes.

� Robust algorithms to search solutions that can sustainto input variations/uncertainies.

� Hybrid algorithms that interleave global and localsearch (Memetic Algorithm) or embed domainknowledge, e.g. shifting bottleneck detection.

Amos Ng

OPTIMISE : A Research Platform

Scandinavian Organisation of Logistics Engineers

(SOLE)

1. What is simulation-based optimisation and why

2. Why OPTIMISE: an industrial perspective

3. Why OPTIMISE: a research perspective

4. Overview of some industrial test cases

5. The PRiTSi test case with Posten

Presentation Agenda :

Amos Ng

8 Real-life Test Cases

1. Posten AB: Prosit

2. Posten AB: PRiSTi

3. Volvo Aero: Multi-Task Cell

4. Volvo Aero: Multi-Task Cell weekly planning

5. Volvo Cars Engine, Skövde: L-factory

6. Volvo Cars Engine, Skövde: H-factory

7. Volvo Powertrain, Skövde: D31 DOE

8. Volvo Powertrain, Skövde: D31 Optimisation

Amos Ng

Real-life Test Cases

Amos Ng

Optimal buffer allocation in Volvo Cars Engine

� Multi-objective optimisation for L-factory through buffer allocation:

• 7% higher throughput, decreased WIP and higher delivery performance.

Amos Ng

OPTIMISE for camshaft machine scheduling

Amos Ng

Cell Optimisation for Volvo Aero

� Volvo Aero Optimization of Multi-Task cell

• Higher utilization average 10%, decreased product delay time, decreased number of delayed products.

Amos Ng

Simulation Model for Multi-Task Cell

Amos Ng

Test case with Posten: Prosit

� Scheduling of automatic post sorting programs

� Objective: Search the optimal sorting programs schedule that can reduce cost, increase machine utilisation with minimal delay.

Amos Ng

The OPTIMISE client for Prosit

Scandinavian Organisation of Logistics Engineers

(SOLE)

1. What is simulation-based optimisation and why

2. Why OPTIMISE: an industrial perspective

3. Why OPTIMISE: a research perspective

4. Overview of some industrial test cases

5. The PRiTSi test case with Posten

Presentation Agenda :

Amos Ng

Case PRiTSi med Posten

� Optimering av transportupplägg över hela Sverige

� Att manuellt hitta optimala transportupplägg är ohyggligt komplex

� Att bara hitta ett ”hyfsat” transportupplägg manuellt är mycket krävande

� Syfte med testcaset: Att ta fram en applikation som automatiskt genererar och optimerar transportupplägg

Amos Ng

Brevdistributeringsprocess

Amos Ng

Brevdistributeringsprocess

1. Collection Boxes

5. Intra-regional Transportation

3. Inter-regional Transportation

7. Distribution to Recipents

2. Mail Processing Facilities

4. Mail Processing Facilities

6. Mail Carrier Centres

Amos Ng

Problemrepresentation

Tåg

Flyg

Bil

Lastbil

Till varje kant associeras:

Maxvolymv

Tidt

Miljöpåverkanp

Kostnadc

Maxvolymv

Tidt

Miljöpåverkanp

Kostnadc

Typ av kanter:

Lastbil + släp

Amos Ng

Omlastningspunkter kat. 1

Amos Ng

Transportupplägg

� En sträcka består av en eller flera delsträckor. En sträcka börjar alltid på en terminal eller en omlastningspunkt kategori 1 och slutar alltid påen terminal.

� En transport består av en sträcka och en starttid.

� Ett transportupplägg består av ett antal transporter. Transportupplägget är alla transporter som kommer att köras i simuleringen.

Amos Ng

Målet av Optimering

� Målet med optimeringen är att ta fram det bästa transportupplägget med hänsyn till antal brev som kommer fram i tid, transportkostnad och miljöpåverkan

� Krav för ett giltigt transportupplägg:

� Hänsyn måste tas till de regler för samlastning som finns

� Bara de transportrelationer som finns definierade får användas

� Fordons maxkapacitet får ej överträdas (Observera att det ej är ett krav att samtliga deadlines hålls, men det är önskvärt)

� Utnyttjande av omlastningspunkter uppmuntras

� Om det inte är möjligt att få fram vissa brev i tid ges mer belöning ju närmare målet breven kommer

Amos Ng

In- och utdataskal

Amos Ng

Optimeringsalgoritmer

� Två optimeringsalgoritmer används

� “Hill climber” för lokal sökning

� Genetisk algoritm för global sökning

� Heuristiker används i algoritmerna

� Utnyttjande av omlastningspunkter uppmuntras

� Om det inte är möjligt att få fram vissa brev i tid ges mer belöning ju närmare målet breven kommer

Amos Ng

Arbetsgång

� Problem: Det krävs en mycket stor mängd simuleringar för att hitta bra lösningar och varje simulering är tidskrävande

� Lösning: Grovsimulering� Ger mycket snabbt ett ungefärligt värde på resultatet

Amos Ng

OPTIMISE Clienten för PRiTSi

Scandinavian Organisation of Logistics Engineers

(SOLE)

Questions?