Issues%20in%20Dynamic%20Fleet%20Management

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Issues in Dynamic Fleet Management

• Talk at
• ROUTE 2000 - INTERNATIONAL WORKSHOP ON VEHICLE
  ROUTING
• SKODSBORG, DENMARK - AUGUST 16-19, 2000
• Geir Hasle
• Research Director, Department of Optimization
• SINTEF Applied Mathematics
• Oslo, Norway
• Geir.Hasle_at_math.sintef.no
• http//www.oslo.sintef.no/am/

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My talk

• SINTEF Applied Mathematics (SAM)
• Fleet Management
• industrial potential, status, requirements
• technology
• research, science
• bridging the gap between science and industry
• Challenges
• Routing etc. at SAM
• Research Agenda

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SINTEF The Foundation for Scientific and
Industrial Research at the Norwegian Institute
of Technology
The vision Technology for a better society
Business concept SINTEFs goal, in co-operation
with NTNU and UiO, is to meet needs of the
private and public sectors for research-based
innovation and development
Locations The SINTEF Group have 1800 employees,
400 in Oslo and 1400 in Trondheim.
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SINTEFs council
SINTEFs board
President/Vice-president
SINTEF Applied Mathematics
SINTEF Petroleum Research
SINTEF Civil and Environmental Engineering
MARINTEK The Norwegian Marine Technology Research
Institute
SINTEF Electronics and Cybernetics
SINTEF Applied Chemistry
SINTEF Energy Research
SINTEF Materials Technology
SINTEF Fisheries and Aquaculture
SINTEF Industrial Management
SINTEF Telecom and Informatics
SINTEF Unimed
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SINTEF-Group turnover in 1999
Basic grants from The Research Council of
Norway 3,3
Strategic programs from The Research Council of
Norway 4,3

• Contracts 92,4
• - Industrial and commercial enterprises 53,0
• - Public sector 12,5
• - International contracts 10,5
• - The Research Council of Norway (project
  grants) 9,9
• - Other sources 6,5

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SINTEF Applied Mathematicshttp//www.oslo.sintef.
no/am

• A contract research institute in the SINTEF group

Geometry
Modeling
Simulation
Optimisation
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SINTEF Applied Mathematics Department of
Optimisation
Focus Applied research Planning Decision Support
Basis Knowledge Based Systems Operations
Research Computing science
Application types Resource optimisation Design/co
nfiguration Discrete
Main business areas Transportation Area
management Oil business Manufacturing
Approach Generic Tools Reuse Methodology
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Transportation of goods in Norwayand EU

• 12.000 companies (EU 1/2 mill.)
• Annual turnover 30 billion. (EU 1.200 billion.)
• Many SMEs
• 36 empty driving
• Capacity utilization with load 60
• Logistics costs 12 of product costs (EU 7)
• EU 13 million trucks, 800 billion ton-kilometers
  (1990)
• Germany freight income some 60 billion DM (1990)

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Industrial use of VRP Tools

• Excess travel, huge potential
• Swedish report 1999 (commercial road transport)
• large end users, food beverage
• generation of static routes
• vendors claim operational tools
• very high potential for savings
• A. Henriksson, P. Liljevik Dynamisk
  ruttplanlegging i verkligheten
• Minirapport MR 123, TFK - Institutet för
  transportforskning, Stockholm October 1999

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Increasing need for VRP Tools

• focus on
• time
• cost
• utilization
• customer service
• lead time reduction
• reactivity
• regulations, environmental concerns
• e-commerce, home shopping

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Reasons for mismatch

• lack of awareness in industry
• lack of data and infrastructure
• price (SMEs)
• organizational problems, resistance
• practical constraints
• information availability
• physical movement
• tools not good enough
• functionality, modelling power
• user friendliness
• integration
• logistical performance

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Existing tools - keywords

• Large variety simple TSP - sophisticated VRP
  solvers
• focus road transportation of goods, local
  distribution
• built for operative planning, used for generation
  of static routes
• packages
• primitive integration, but good import facilities
• inflexible and simple or heavy on consultancy
• Windows-platform
• good user interfaces, map visualization, manual
  changes
• VRP algorithms?
• real-time planning?
• multiple users?
• continuous optimization?
• priced at USD 40.000 and above (high end)

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Some Vendors

• Descartes Systems USA
• Caps Logistics -gt Baan USA
• MicroAnalytics USA/GB
• Roadnet Technologies (UPS) USA
• i2 USA
• ESRI USA
• Kositzky and Associates USA
• Manugistics USA
• Carrier Logistics Inc USA
• Insight Inc. USA/The Netherlands/GB
• Caliper Corporation USA
• Trapeze Software Group USA/Canada
• Giro Canada
• DPS International UK
• Paragon Software Systems UK
• Optrak (Andersen Consulting) UK
• Ilog F
• Diagma F
• PTV D

Typically claim 10 - 30 cost reductions - static
routes
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Few VRP Tools in Operation in Norway

• Coca-Cola
• Taxi companies
• Falken
• NAS
• NKL
• Tollpost-Globe
• Linjegods
• Postal service
• Hydro Agri

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Challenges - VRP Tools

• Functionality
• Modelling
• constraints
• criteria
• uncertainty
• dynamics
• supply-chain coordination
• Adaptability
• Power speed vs. quality
• Large-size problems
• User Interface
• Integration
• Support etc.

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Dynamic, real-time routing - Success stories?

• Paragon - Tesco
• Home shoppers simply log onto the dedicated
  area of Tesco's website, select their purchases
  and identify a two hour time window for delivery
  to an address of their choosing ...
• Truckstops
• In some UK applications it is even used to
  recalculate routes during the day, modifying its
  original calculations to take account of new
  requirements and reflecting data transmitted back
  from vehicles by radio
• PriceWaterhouseCoopers

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Goal - VRP Technology

• real benefits for industry - logistical
  performance
• solve right problem
• plan quality vs. response time
• user interaction, user-friendliness
• configurability
• reactivity
• price

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Future VRP technology

• GIS vendors
• ERP vendors
• ASP solutions, thin clients, Internet, www
• better tools for strategic/tactical planning
• supply-chain coordination, integrated solutions
• dynamic, real time fleet management

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Dynamic Fleet Management - Prerequisites

• ICT infrastructure
• order data
• fleet data
• access to high quality traffic data
• speed predictions
• organic electronic road network
• Better understanding of routing policies
• Better VRP algorithms

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Issues in VRP research

• Large, ill-structured problems
• rich models
• uncertainty
• dynamics
• multiple criteria
• reactivity
• disruption?
• slack
• policies
• plan quality vs. response time performance
• decomposition
• human issues

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Stochastic and dynamic VRPs

• what does dynamic mean?
• problem changes dynamically
• Psaraftis (1995) ... information on the problem
  is made known to the decision maker or is updated
  concurrently with the determination of the set of
  routes.
• Baita, Ukovich, Pesenti, Favaretto (1998) ...
  releated decisions have to be taken at different
  times within some time horizon, and earlier
  decisions influence later decisions.
• a.k.a. real-time, on-line
• organic routing plans
• challenges
• information flow
• physical goods
• good idea? (talk of Carlos Daganzo)

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Literature - dynamic VRPs

• 6 INFORMS sessions since 1995, some 20 papers
• some 50 journal papers

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Some papers

• Psaraftis (1995) Dynamic vehicle routing Status
  and prospects
• Bertsimas, DJ / SimchiLevi, D (1996) A new
  generation of vehicle routing research Robust
  algorithms, addressing uncertainty
• Crainic, TG / Laporte, G (1997) Planning models
  for freight transportation
• Baita, F / Ukovich, W / Pesenti, R / Favaretto, D
  (1998) Dynamic routing-and-inventory problems A
  review
• Swihart, MR / Papastavrou, JD (1999) A
  stochastic and dynamic model for the
  single-vehicle pick-up and delivery problem
• Savelsbergh, M / Sol, M (1998) Drive Dynamic
  routing of independent vehicles
• Ioachim, I / Desrosiers, J / Soumis, F /
  Belanger, N (1999) Fleet assignment and routing
  with schedule synchronization constraints
• Gans, N / VanRyzin, G (1999) Dynamic vehicle
  dispatching Optimal heavy traffic performance
  and practical insights
• Reiman, MI (1999) Heavy traffic analysis of the
  dynamic stochastic inventory-routing problem
• Gendreau, M / Guertin, F / Potvin, JY / Taillard,
  E (1999) Parallel tabu search for real-time
  vehicle routing and dispatching
• Powell, WB / Towns, MT / Marar, A (2000) On the
  value of optimal myopic solutions for dynamic
  routing and scheduling problems in the presence
  of user noncompliance
• Cheung, RK / Muralidharan, B (2000) Dynamic
  routing for priority shipments in LTL service
  networks
• Gendreau, M / Laporte, G / Seguin, R (1996)
  Stochastic vehicle routing
• Gendreau, M / Laporte, G / Seguin, R (1996) A
  tabu search heuristic for the vehicle routing
  problem with stochastic demands and customers
• Haughton, MA (1998) The performance of route
  modification and demand stabilization strategies
  in stochastic vehicle routing
• Yang, WH / Mathur, K / Ballou, RH (2000)
  Stochastic vehicle routing problem with
  restocking
• Haughton, MA (2000) Quantifying the benefits of
  route reoptimisation under stochastic customer
  demands
• Secomandi, N (2000) Comparing neuro-dynamic
  programming algorithms for the vehicle routing
  problem with stochastic demands
• Shieh, HM / May, MD (1998) On-line vehicle
  routing with time windows - Optimization-based
  heuristics approach for freight demands requested
  in real-time

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Approaches - uncertainty, dynamics

• ignore
• deterministic model - and repair
• crisp, optimized plans are brittle
• is disruption costly?
• add slack, how?
• stochastic model
• investigation of policies
• still need dynamic decision-making
• lessons to be learnt from factory scheduling

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Dynamic VRP DSS

• dependent on high quality updated information
• fleet status
• order status
• organic route planning
• concept of current plan
• when do we commit?
• when do we include changes?
• locking parts of plan
• do we need to worry about disruption?
• dependence on type of operation / business rules
• delivery vs. pickup
• applicable algorithms
• (how much) do we save by taking a dynamic
  approach?

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Approaches

• insertion heuristics iterative improvement
• constraint propagation
• MP formulations?
• Minimal disruption possibly an additional goal
  criterion component

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Routing at SAM

• SPIDER
• GreenTrip
• HAMMER - vessel routing with inventory
  constraints
• Bus scheduling
• eCSPlain, EU FP V
• Distributed problem solving
• Proposals

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SPIDER

• a VRP Solver C program library
• UNIX
• Windows
• COM component
• instantiates to a module for optimised transport
  management
• plan-administrasjon
• VRP optimisation
• cheapest path calculations
• adaptable to wide variety of applications
• distribution through sw vendors

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GreenTrip

• Esprit 20603, January 1996-March 1999, gt 40
  person-years
• Consortium
• Tollpost-Globe (N)
• Pirelli (I)
• Ilog (F)
• University of Strathclyde (GB)
• SINTEF (N)
• RTD effort in methods, algorithms, and generic sw
  for optimised fleet management

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The goal of GreenTrip

• Produce a cost-effective tool to optimise routing
  of vehicles that
• is generic
• takes into account multiple business constraints
• permits efficient (re)configuration
• integrates easily in existing IT infrastructure

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GreenTrip Technical Approach

• OO Programming
• Constraint Programming
• Iterative Improvement Techniques
• Applications Modelling
• Automated Systems (Re)Configuration

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The GreenTrip Consortium
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CASE TOLLPOST-GLOBE

• Pick up orders 600
• Regular and non-regular customers
• Deliveries 2.400
• Time windows - Customer service
• Two days are not the same
• some 100 vehicles
• Different vehicles (size, volume, equipment)
• Depot with automatic sorting / registration

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CASE TOLLPOST-GLOBE

• Electronic road and address data are available
  via the GIS Transportation Demonstrator
• Mobile communication installed in 15 vehicles
• GPS installed in 5 vehicles
• some 100.000 customers in the Oslo region
• goal dynamic fleet management system

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The Pirelli (Cables) Case

• Logistics network simulator
• Assessment of logistical performance
• Detailed analysis of alternative structural
  changes
• scenarios 6 months operation, 10.000 orders

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GreenTrip - GGT Systems Architecture
Application Server
VRP Solver
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The VRP Solver - Objects

• Plans
• Locations
• Visits
• Vehicles
• Routes
• Dimensions
• Constraints

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VRP Solver - Algorithms

• Construction
• Savings
• Sweep
• Nearest ...
• Improvement, move operators
• 2-opt, Or-opt
• Relocate
• Exchange
• Cross

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VRP Solver - Search Control

• Basic heuristic
• Greedy Search (First Improvement)
• Steepest Descent (Best Improvement)
• Meta-heuristics
• Tabu Search
• Guided Local Search
• Guided Tabu Search

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GreenTrip - Results

• VRP Solver -gt ILOG Dispatcher
• GGT -gt GreenTrip AS Dynamic planner
• best-until-now results on OR benchmarks
• Industrial Test Cases
• Publications
• some 20 scientific papers
• reports - VRP Solving and IIT Survey

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GreenTrip Dissemination

• Kilby, Prosser, Shaw Guided Local Search for
  the VRP, Proc. MIC 97
• De Backer, Furnon Metaheuristics in Constraint
  Programming Experiments with Tabu Search on the
  VRP, Proc. MIC 97
• De Backer, Furnon, Kilby, Prosser, Shaw Local
  Search in Constraint Programming Applications to
  vehicle routing problems, CP 97 Scheduling
  Workshop
• Hasle GreenTrip - the Development of a Generic
  Toolkit for Vehicle Routing, NOAS 97
• De Backer, Furnon Solving vehicle routing
  problems with Side Constraints Using Constraint
  Programming, INFORMS 97
• De Backer, Furnon Modelling pickup and delivery
  problems in constraint programming, INFORMS 98
• Bouzoubaa, Hasle, Kloster, Prosser The GGT a
  Generic Toolkit for VRP Applications and its
  Modelling Capabilities, Proc. PACLP 99

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GreenTrip Papers

• De Backer, Furnon, Kilby, Prosser, Shaw Solving
  vehicle routing problems with constraint
  programming and metaheuristics, Journal of
  Heuristics, Special Issue on CP
• Kilby, Prosser, Shaw A comparison of
  traditional and constraint-based heuristic
  methods on vehicle routing problems with side
  constraints, Constraints, April 98
• De Backer, Furnon Local Search in Constraint
  Programming, in META-HEURISTICS Advances and
  Trends in Local Search Paradigms for
  Optimization (Voss, Martello, Osman, Roucairol,
  1999)
• Kilby, Prosser, Shaw Guided Local Search for
  the Vehicle Routing problem with Time Windows,
  in META-HEURISTICS Advances and Trends in Local
  Search Paradigms for Optimization (Voss,
  Martello, Osman, Roucairol, 1999)
• Kilby, Prosser, Shaw Dynamic VRPs A Study of
  Scenarios (forthcoming)

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Vessel Routing - Ammonia

• Norsk Hydro Agri
• Producer - Consumer Harbours (25)
• Fleet (10)
• Strong Inventory Constraints
• External Trading
• Feasible solution
• Earlier approach MIP
• Approach taken Heuristic Sequencing LP

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HAMMER Problem
Producing harbours
Quantity Time-window
Consuming harbours
External orders (laycans)
Fleet of vessels
Harbours with stock inventory
Find the routing plan with the lowest cost so
that inventory limits are not exceeded and all
external orders included.
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Combinatorial solution
Vessel View
Harbour View
3
2
H1
6
H2
H3
1
4
7
H5
H6
H7
5
Site
Route for Vessel 1
Vessel 1
Route for Vessel 2
Vessel 2
Harbour View Which vessels, and in which
sequence, will call at each harbour.
Vessel View Which harbours, and in which
sequence, each vessel will visit.
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HAMMER - Linear solution
Vessel view Harbour view
max
Load
min
Time
Call
Stock
Time
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HAMMER - System overview
Problem data
Initial solver
Iterative improver
Combinatorial solution
Feasibility check
Greedy Propagator
Feasible solution
LP solver
Update
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HAMMER - Working with the system

• Initialisation of the problem
• Harbours, ships, laycans and planning parameters
• Schedule generation
• Initial solver - from scratch or existing
• Iterative improvement
• Analysis and user interaction
• plan statistics - slack, unserviced
• manually change plan
• Lock ship, harbour or time period
• Flatberg, Haavardtun, Kloster, Løkketangen.
  (2000) Combining exact and Heuristic methods for
  solving a Vessel Routing Problem with inventory
  constraints and time windows. To appear in
  Ricerca Operativa, special issue on combined
  constraint programming and OR techniques

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Research Agenda SAM VRP

• construction heuristics
• construct and improve
• restart
• greedy limited backtracking
• IIT by local search and meta-heuristics
• exact methods subproblems / limited problems
• hybrid methods
• dynamic VRP
• empirical investigation

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Important topics, SAM

• configuration of transportation networks
• VRPs and TSPs with side constraints in road based
  and maritime transportation
• cheapest path problems in large, dynamic network
  topologies
• Proposal to Research Council of Norway

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Research Agenda SAM Optimisation / CSP

• over-constrained problems
• multi-criterion problems
• supply-chain coordination
• distributed problem solving

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Research Agenda VRP

• rich models, large problems
• dynamic VRPs
• exact methods for limited (sub)problems
• over-constrained problems
• multi-criteria problems
• methodology problem type - algorithm
• cooperating VRP solvers, hybrid methods
• decomposition

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Issues in Dynamic Fleet Management

• Talk at
• ROUTE 2000 - INTERNATIONAL WORKSHOP ON VEHICLE
  ROUTING
• SKODSBORG, DENMARK - AUGUST 16-19, 2000
• Geir Hasle
• Research Director, Department of Optimization
• SINTEF Applied Mathematics
• Oslo, Norway
• Geir.Hasle_at_math.sintef.no
• http//www.oslo.sintef.no/am/