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abi 3 l First Advisory Panel Meeting Dr Liz Varga liz.varga@cranfield.ac.uk PowerPoint Presentation
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abi 3 l First Advisory Panel Meeting Dr Liz Varga liz.varga@cranfield.ac.uk

abi 3 l First Advisory Panel Meeting Dr Liz Varga liz.varga@cranfield.ac.uk

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abi 3 l First Advisory Panel Meeting Dr Liz Varga liz.varga@cranfield.ac.uk

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  1. abi3l First Advisory Panel Meeting Dr Liz Varga liz.varga@cranfield.ac.uk 25th Nov 2010

  2. Agenda • 10:00 Welcome and intro to abi3l plus role of panel - LV and AB • 10.10 The challenges for freight strategy in a constrained financial environment – MG and AB • 11:00 Strategic Modeling software and break-out session 1 – SV • 11.40 Coffee • 12:00 Feedback from breakout session 1 • 12:30 Agent based technology – principles and cases – PG • 13:00 Complex Systems Research Centre past models – LV and PA • 13.15 Lunch • 14:00 Introduction to proposed model structure – PG • 14.45 Breakout session 2 • 15.15 Coffee • 15:30 Feedback from breakout session 2 • 16:00 Close

  3. AGENT BASED INTELLIGENT LOGISTICSabi3l Partners MDS Transmodal - lead Cranfield University LCP Consulting Barloworld Supply Chain Software Part funded by the Technology Strategy Board 209083_presentation251110

  4. What is abi3l? • - an attempt to employ agent based modelling to the freight industry • What is Agent Based Modelling? • forecasting on the basis of the behaviour of decision makers • Why try? • because existing methods are normally optimisation exercises for individual actors • but the freight industry is far more complex

  5. Defining the freight industry • All those companies & authorities facilitating and initiating the movement of freight • Infrastructure owners & operators • Equipment owners & operators • End users • In practice • Retailers & wholesalers • Ports • Shipping lines • Hauliers • Train operators • Forwarders • 3PLs • Road and rail network providers • Developers • The decisions each make define the opportunities available to the rest • Freight almost entirely in the private sector

  6. The challenge for freight investment policy • Carbon reduction and freight’s contribution

  7. The challenge for freight investment policy … • Economic value from freight and logistics • 5% of the total vehicle parc create 25% of emissions • 5% of the vehicle parc creates up to 50% of the congestion on the national network • Tonne-kms have decoupled but more will be needed

  8. The challenge for freight investment policy … • Radical solutions are needed and will not be enough • Will need to re-design networks to reduce T-kms

  9. The challenge for freight investment policy … • Network investment will be increasingly private as public spending commitments are reduced

  10. Policy elements • …to drive change • Regulation • Fiscal measures • Planning • Private investment • Public investment • Complex interactions – difficult choices

  11. Arguments for modelling & forecasting • For the State • To get policies on taxation & investment • To regulate • To satisfy international agreements re climate change • To promote economic efficiency • Only achievable through understanding private sector business decisions • For the private sector • To make optimum investment decisions based on the behaviour of the other actors • To accelerate pace of change by understanding how other actors behave, reducing risk

  12. Illustrating interactions • The more deep sea port development in the South East • The better the case for rail freight terminals in Northern England • The more rail freight activity • The better the case for warehouse development on rail linked sites • The more rail linked sites • The more skeletal trailers required • The more rail network capacity required • The faster imports grow from the Far East • The more deep sea port development • But where should be? • A complex system!

  13. Our process • To establish interactions within the industry • A matrix of relationships • Populated by companies • To populate those relationships with data • Synthetic cargo flows • Transport costs • To model interactions • Modify parameters • To produce a calibrated model

  14. Data sources • Through GB Freight Model/State • Continuing Survey Road Goods Transport • Network Rail • Maritime Statistics • Customs & Intrastat • Privately sourced • Generic data on production & consumption

  15. Our offer to the Panel • In exchange for advice on interactions in the industry • To provide insight into the outcomes of our modelling and the applicability of the tool • Our goal is to produced a suite of pilot models for different actors in the chain

  16. Agenda 10:00 Welcome and intro to abi3l plus role of panel - LV and AB 10.10 The challenges for freight strategy in a constrained financial environment – MG and AB 11:00 Strategic Modeling software and break-out session 1 – SV 11.40 Coffee 12:00 Feedback from breakout session 1 12:30 Agent based technology – principles and cases – PG 13:00 Complex Systems Research Centre past models – LV and PA 13.15 Lunch 14:00 Introduction to proposed model structure – PG 14.45 Breakout session 2 15.15 Coffee 15:30 Feedback from breakout session 2 16:00 Close

  17. Strategy and software • Strategic Software modeling • Strategic, Tactical & Operational Models • Software Approaches • Strategy Formulation – Optimization Vs Robustness • Breakout Session – Format for response

  18. Freight Software Document Inclusion Existing modelling software

  19. Software Approaches • Evaluation/Simulation – Base position – Prescribing alternative Solution • Optimization – Optimization Engine *Based on internal data and evaluated after the event

  20. Strategy Formulation • Optimization Vs Robustness Optimization may drive seemingly appropriate strategic decisions in the form of capital investment yet does not mitigate risk • 3663 Example 18.5 ton vehicles purchased to consolidate distribution (right decision at time) Category growth in the Chilled product group *In an uncertain world – awareness the whole picture matters!!

  21. Strategy • Matching Capabilities – Against Environment Understanding the environment (today & tomorrow) is fundamental to success

  22. Break Out SessionStrategic Decision Making Process • External Factors • Identification • Incorporation • Of ‘knowledge’ • Simulation of impact • Consultancy • applicable to your business? • how, where, for what?

  23. Briefing Documentfor breakout session – Strategic Modelling Software • Identification – External factors to Strategic Planning, including innovations/technology, market data, competitor activity, research, government legislation, infrastructure limitations, etc • Incorporation – How do I use the above information? What data is considered critical? How do I attribute relevance/importance to the above factors? (what factor is most important to me?) • Simulation – Do I or can I model the potential impact of the above drivers to understand impact? What do I use to do so? • Consultancy - What resources do I utilise, external/internal . Why do I value these resources? Where are they best used?

  24. Agenda 10:00 Welcome and intro to abi3l plus role of panel - LV and AB 10.10 The challenges for freight strategy in a constrained financial environment – MG and AB 11:00 Strategic Modeling software and break-out session 1 – SV 11.40 Coffee 12:00 Feedback from breakout session 1 12:30 Agent based technology – principles and cases – PG 13:00 Complex Systems Research Centre past models – LV and PA 13.15 Lunch 14:00 Introduction to proposed model structure – PG 14.45 Breakout session 2 15.15 Coffee 15:30 Feedback from breakout session 2 16:00 Close

  25. Challenges & opportunities of complex environments • How do we recognize complexity and why do we need to approach it differently? • Why bother? • What’s been done so far? • What does good look like?

  26. Why bother Very hard to model using formulas – because its all about autonomous behaviour • Possible model if we accept simple rules for each agent • I want to survive (objective/goal) • Crashing is bad • Crashing with big things is very bad • And allow them to adapt by: • Choosing when to brake • Choosing when to accelerate If agents learn accelerating into something big hurts then they brake when they are approaching a bus

  27. Freight networks are similar The network is “self-organising” Warehouses are built without co-ordination Rail, road, and port investments are not co-ordinated Freight movements at a national level are not co-ordinated Policy is modally focused Outcomes are therefore not predicted but emergent

  28. Interdependencies Transport Policy Modal Investments Ship Road Rail CO-EVOLUTION Modal Capacity Modal Choices

  29. Some examples of ABM & Freight

  30. Collaboration in Freight Cost 1 Cost 2 Cost 3 Adapted from: Krajewska & Kopfer (2006)

  31. Collaboration in Freight • Trivial until : • Large no of manufacturers • Large no of freight consolidators • Capacity constraints • Accumulation of benefits • Different contract lengths • Negotiation • Different pricing strategies Cost 1 Cost2/2 < Cost 1 Cost 3 • Optimal number of freight forwarders ? • Too many and scale effects are minimal • To few and power influences pricing strategy Adapted from: Krajewska & Kopfer (2006)

  32. Investment decisions • What rules work best and when do they work best? • Long term investment • Short term investment • Which vessel types should be invested in and when? • Handysize • Panamix • Capesize Demand Recoverable price New Price Fleet mix • First mover benefits • Differentiated rules by vessel type Adapted from: Engelen et al (2010)

  33. Behaviour and policy interactions Agents allowed to plan routes under different policies – motorway charging and no charging Agents that were allowed to make mistakes learned faster and outperformed those that didn’t make mistakes Policy frameworks that incorporate learning are more likely to achieve their objectives Adapted from: Liedtke (2009)

  34. What makes a good freight model • Incorporates behaviour (choice & learning/adaptation • Multi-modal • Incorporates feedback • Integrates freight and passenger travel • General and not too specific Source: Hedges (1971)

  35. Literature review Most of the literature describes frameworks

  36. Modelling frameworks (single Layer) Business Unit Agent Attributes Assets Processes • 1 Level of inter-agent relationship • Each Agent has a set of: • Assets • Attributes • Processes Business Unit Agent Attributes Assets Processes

  37. Modelling frameworks Multiple Layers Business Unit Agent Business Unit Agent Attributes Attributes Assets Assets Function Agent Function Agent Function Agent Function Agent Processes Processes Processes Processes Each business unit agent has relationships with its own functional agents, and either separately or collectively the business unit/function agents form relationships with other business unit/function agents

  38. Summary • Freight movement plays out on a rich landscape incorporating many agent types • The freight landscape incorporates many dependencies • Freight agents make autonomous decisions with limited knowledge of the big picture • Limited visibility requires constant adaptation to an ever changing environment

  39. Agenda 10:00 Welcome and intro to abi3l plus role of panel - LV and AB 10.10 The challenges for freight strategy in a constrained financial environment – MG and AB 11:00 Strategic Modeling software and break-out session 1 – SV 11.40 Coffee 12:00 Feedback from breakout session 1 12:30 Agent based technology – principles and cases – PG 13:00 Complex Systems Research Centre past models – LV and PA 13.15 Lunch 14:00 Introduction to proposed model structure – PG 14.45 Breakout session 2 15.15 Coffee 15:30 Feedback from breakout session 2 16:00 Close

  40. Logistics, Complexity and Modelling • Cranfield’s Complex Systems Research Centre

  41. Overall Development depends on Multiple Scales • In reality - National is sum of Regional – which is sum of local etc. Structure is multi-scaled! • Structure is driven by decisions and policies concerning factors such as: Economic activities, salaries, rents and taxes. Industry, commerce, manufacturing, retail, services, finance…. • Logistics reflect and affect the distribution of people, ages, employment, education, crime, travel, patterns of demand, family size, health, lifestyle, unemployment etc.

  42. Can we build an “emergent” distribution system? Cost of production • Can we build a system that will itself design and adapt its structure over time? • It will need to represent the way that the many actors in the system operate, and how their actions affect each other. Costs of transport To Showroom Costs of Showrooms Costs of getting To Customer

  43. Simple Case Study:Photocopiers across the UK We can model the emergence of distribution centres These might be warehouses or depots or might be centres of repairs, spare parts etc.

  44. Actual Photocopier Distribution Centres The Case Study modelled had actual distribution centres as above The questions asked are: How many Centres should there be? Are the ones we have in the right places?

  45. What goes into the model? • Factory Gate prices • Costs of distribution to showrooms • Costs of showrooms (Fixed and variable) – with unit costs falling with volume • Road Network distance to customers

  46. A Self-OrganizingModel • Demand is considered to be proportional to the population • Distances are calculated using road networks that can provide both distance and time of travel • Costs of warehousing depends on density of land-use • Cost/unit of goods transfer depends on volume

  47. Mathematics…….. Production at k Centre i Customer l at j Attractionl(i,j) = attraction of Centre i as viewed by customer of type l located at j. R = Rationality (linked to homogeneity of customers l, information…) Price(i) = Factory Gate Price(k) + Transport Costs to Centre i from k + costs at i. Factory Gate Price (k) = Capital costs, land, labour at k Costs at Centre i = Capital Costs, land, labour at i

  48. Customers Choice Running Model forward Random Attractors, + Behaviours Routines Price Node Volume Knowledge Generation Under different levels of disturbance Can use a Model to create “emergent structure”:

  49. Can be a multi-level model: • We can use the same type of program to build a multi-level set of centres • This could test the advantage of having major points of distribution, or even having several levels • It can tell us how many levels are necessary • This will only apply if there are economies of scale in the transportation at different levels

  50. Improved Transport Infrastructure for West Bengal • Work with Asian Development Bank for West Bengal • Survey by Halcrow Consultants of the current flows of goods on the roads • Transport Infrastructure projects: effects on transport costs. • Economic gains lead to increased consumption and production. Spatial multipliers on jobs created allows calculation of the “impact on poverty” – where and how much extra employment and wealth created