Intermodal Transportation
Teodor Gabriel Crainic
ESG UQAM &
Plan
à What are we talking about?
à Container-based intermodal transportation à System design (location)
à Fleet Management (empties) à Perspectives
Intermodal Transportation
à Simple and straightforward definition:
à Movement of a person or a load by a sequence of at least
two transportation modes, the transfer from one mode to the next being performed at a (intermodal) terminal
à E.g., Door-to-door transportation of containers ÓOver long distances
ÓOrigin → “land” transport → port → container ship
A “Strict” Definition
à Movement of goods
à One and the same loading unit or vehicle à A chain of
à Several transportation modes (services) ÓCoordination
ÓInteractions
à Intermodal terminals
ÓNo handling of the goods themselves à Door-to-door service
A More General Definition
à Movement of goods à A chain (network)
à Several transportation modes (services) ÓCoordination (more or less)
ÓInteractions
à Intermodal terminals à “Door-to-door” service
Many Things to Many People
à Major instrument for E.U. policy aimed at switching
freight from trucks & highways to more environment-friendly modes (rail, water)
à Dedicated rail services (subdivisions) to move large
volumes of containers/trailers over long distances: the trans-continental “land bridges”
à Container transportation
à Consolidation carriers: local & long-haul operations,
several long-haul types of services, with/without use of external services
Many Things to Many People
(2) à Uncontainerized cargoà Courier (express) services à National planning
à City Logistics
Scope of Presentation
à Container-based intermodal transportation
ÓIllustrative planning/operations management issues
ÓOperations research models and methods
à A very young field à No definite answers
Plan
à What are we talking about?
à Container-based intermodal transportation
à System design (location)
à Fleet Management (empties) à Perspectives
Intermodal Transportation – Containers
à Advantages
ÓReduced cargo handling
ÓIncreased security regarding damage and loss ÓIncreased standardization of transportation and
transfer equipment
ÓIncreased automation of terminal operations ⇒Cost reduction, more efficient door-to-door
transportation
Evolution of Container Traffic
(Koh and Kim 2001) 5.8 254.6 2003 Growth rate (%) Container traffic (M) Year 3.9 240.6 2002 2.8 231.6 2001 10.9 225.3 2000 10.0 203.2 1999 4.2 153.5 1997 9.8 137.2 1995 12.5 113.2 1993Intermodal Transportation – Containers
(2) à Lifeline of world-wide trade and economyà Increasingly larger container ships for inter-continental
transportation (liners)
ÓThese cannot berth at all ports
ÓIt is not economical to stop at many ports à Container mega ports
à New coastal navigation feeder services (“regular” ships):
mega ports and huge liners ↔ regular ports
⇒A new link in the multi-modal chain
Intermodal Transportation – Containers
(3)Þ Asia (Hong Kong, Singapore, …) to America or Europe: à Origin → truck → port → large container ship (liner)
→ mega port → “small” container vessel → port → truck/rail/river → destination
à Container port terminal transformations for increased
efficiency in loading/unloading operations and exchanges with land carriers
ÓNew terminals / Enhancement of existing ones ÓAutomation
Notes
à Container intermodal transportation
(& express courier / post services)
ÓCustomer: Customized service
ÓOperator(s): Hub-and-spoke network with
consolidation
à All long-haul transportation must address the issue of
empty vehicle repositioning
ÓTrade is unbalanced
⇒Vehicle flows as well !!
Plan
à What are we talking about?
à Container-based intermodal transportation
à System design (location)
à Fleet Management (empties) à Perspectives
System and Service Design
à Strategic decisions – System Design à Locate (intermodal) terminals
à Direct/indirect customer (zone) service à Port/terminal dimensioning
ÓNumber of berths
ÓSize of storage space
ÓType & number of various equipment types à Facility & service abandon, …
System and Service Design
(2) à Tactical decisions – Service DesignÓRoutes served (routes, stops, mode, equipment, …) ÓService frequency & schedule
ÓCargo routing
ÓTerminal workloads
à Container port terminal equipment assignment ÓTo sea-side and land-side operations
System Design
à Not many contributions
ÓTactical or operational models to evaluate strategic
strategies
ÓPorts: queuing, simulation à Discrete location models
ÓConsolidation / hub terminals à Network design + location
ÓSelect direct services/links
à Aim to capture economies of scale associated to
System Design
(2)à Location of facilities (terminals) ÓProduction-distribution
ÓHub location
Location with Balancing Requirements
à Land part of an intermodal container transportation
system (may be generalized)
à Use in-land container depots for more efficient
“Traditional” Operations
Importing customer Exporting Loaded EmptyOperations with In-Land Depots
Importing customer Exporting customer Loaded Empty Empty balancingLocation with Balancing Requirements
(2) à Loaded movements are “profitable”à Empty movements are not
ÓCustomer to depot: Return movement
ISupply of empties
ÓDepot to customer: Demand satisfaction
IDemand for empties
ÓDepot to depot: Repositioning of empty containers
Location with Balancing Requirements Network
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à What are we talking about?
à Brief overview of freight transportation à Container-based intermodal transportation à System design (location)
à Fleet Management (empties)
Operational Planning
à Resource management ÓCrews
ÓVehicles
ÓPower (engines, etc.), and so on à Allocation – dispatching, schedules
ÓMake sure the required resources are where they
need to be when they need to be there
ÓBe efficient !
Issues
à Trade is unbalanced
à Moving goods results in unbalanced distribution of
resources: crews, vehicles, etc.
à One needs to reposition resources for use in the
following periods
ÓRegular operations (if possible)
ÓBalancing operations (vehicles, power units, …) ÓCrews travelling as passengers
Other Operational Issues
à Real-time dispatch à Pacing
à Real-time routing adjustment à …
Consolidation Transportation
à Transportation plan “guides” operations
à It includes guidelines for repositioning (it should …) à “Indicative” schedules: Ad-hoc (real-time) procedures à “Regular” demand planning: Short-term and real-time
adjustment of plans
à Scheduled operations: Repositioning must follow and
“feed” schedules + real-time adjustment
Customized Transportation
à No plan !!
à Dynamic management and control of resources: routes,
schedules, fleets, personnel, etc.
à Uncertainty plays important role ÓDemand
ÓTravel times
ÓService times at customers and terminals ÓWeather, …
The Empty Vehicle Repositioning Problem
à Surpluses and deficits of empty vehicles
ÓObserved at terminals “at the end” of the day
ÓComputed with respect to the next period demand
à Need to reposition for the next period
ÓHow many vehicles (of what type) to move from a
surplus location (origin) to a deficit location
(destination)?
à Much more decision freedom than in loaded
transportation
History
à Transportation model – static and deterministic
ÓKnown surpluses and deficits – No uncertainties ÓNo (not important) travel time impact – Static ÓArrival times known (certain prediction)
IAll travel, loaded and empty, occurs during the same period
ÓSingle or fully substituable resources (vehicles) ÓFor certain LTL types, tactical planning, …
History
(2)à Deterministic, multi-period transshipment model
ÓDifferent movements require different travel times ÓVehicles become empty at different moments
(customer release times)
ÓDemand varies in time …
ÓThe dynamic characteristic of the system represented
through (dynamic, time-dependent) space-time
Space-Time Networks
à Nodes: Facilities – terminals, customers, etc. – at given
time periods
ÓA physical point is repeated at each period & activity
à Arcs: Movements in space and time
ÓIndependent, e.g., a truck moving by itself
ÓGrouped, e.g., containers on flat cars (rail) or in a
ship
Space-Time Network (Simple)
Terminals
Time
Space-Time Network
Terminals
Challenges and Limitations
à One may include ÓCapacities
ÓSeveral types of resources ÓInventory costs
IStock out (rent, borrow, …) IEnd of horizon value
ÓSubstitutions (and costs) ÓComplex cost structures
à Linear programming formulations with a few
Challenges and Limitations
(2)à Planning horizon length? End-of-horizon? ÓRolling horizon
à Everything is deterministic
ÓTimes (travel, terminal operations, customer, …) ÓFuture demand, etc.
à Utilization
The Uncertainty Factor
à Times may vary
à Demand estimation is rarely precise à Unexpected demands and events
à Current decisions impact the future state of the system
and future decisions
à Need to explicitly consider / model
ÓUncertainty – the stochastic nature – of the system
and its environment
ÓThe impact of current decisions on future system state
The Uncertainty Factor
(2)à Stochastic formulations and solution methods
à A complex field: General approaches and, often,
custom-designed methods
à Active research field à Formulations
ÓGeneral stochastic programming and solution
methods :
The Uncertainty Factor
(3)à Formulations
ÓRecourse formulations and rolling horizon methods
INice application to regular-type systems (e.g., consolidation)
ÓStochastic formulation and solution strategies based
on adaptive dynamic (linear) programming and decision/time-based decomposition
ITime-Space multicommodity networks
The Uncertainty Factor
(4)à Challenges of stochastic formulations ÓProblem formulation (!!)
ÓResolution (!!) à Plus
ÓRepresentation of resources and attributes ÓForecasts
ÓAvailability and reliability of data ÓValidation of models and strategies
Container (Empty) Fleet Management
à Major repositioning decisions over large geographical
regions (e.g., inter-continental movements)
ÓSimilar to consolidation transportation à Allocation of empty containers to customers
ÓSimilar to customized transportation à Two applications in this talk
ÓAllocation and management of a heterogeneous fleet
of containers over a land zone
ÓSingle-commodity dynamic container allocation for
Heterogeneous Fleet
à Given region (continent)
à Loaded containers arrive (e.g., maritime network) to be
delivered to customers
à Empty containers arrive or leave to balance system-wide
operations (demand)
à Customers empty containers that must be moved out à Customers require empty containers for future loaded
shipments
Heterogeneous Fleet
(2)à Several types of containers (e.g., 20 or 40 feet, normal
box, thermal, refrigerated, etc.)
à Substitutions allowed: conditions and costs à “Massive” inter-depot balancing movements
à Due-dates at some terminals (e.g., ship schedules) à Time windows at customers
à Demand (at least part of) fluctuates in time and is
forecasted only
à Unloading time at customer: Uncertain
Heterogeneous Fleet
(3)à Containers may be damaged partially (repairs) or totally à External sources (buy, rent) of empty containers
à Centralized empty container fleet management à Loaded movements not “managed”
à Associated problem: global management of the empty &
loaded container movements together with vehicle routes
à A single model not computationally feasible ⇒
Main Movements
(No Time/Container Type Specifics)
Harbour Depot j Depot k Supply customer Demand customer External pool of empty containers
Formulations
à Crainic, Dejax, Gendreau (93)
à Single and multicommodity deterministic formulations à A two-stage, restricted recourse single commodity,
stochastic model
Formulations
(2)à Space-time diagram
ÓGeneralized network (substitutions) ÓMultiple-period transportation arcs ÓHolding arcs (depots)
ÓInter-depot balancing arcs à Stochastic elements
ÓDemand (of known and possible customers) ÓRelease time from supply customers
⇒Inventory levels
Formulations
(3)à Minimize total cost over the time horizon
à Flow conservation (over time and space, including
access to external pool)
ÓSupply at supply customers ÓDemand
ÓContainer substitution
à Depot (and port) inventories (each container type) à Bounds on inter-depot balancing flows
Single Commodity Liner
à Cheung and Chen 1998
à A container liner company offers regular service among
a number of ports
à Carries loaded and, space permitting, empty containers à Ship schedules known and fixed
à 1 ship / period between 2 ports à Demand less than ship capacity à 1 container type
Formulation
à Two-stage stochastic model
ÓTime-space network with random arc capacities ÓMinimize the (expected) total cost
ÓRolling-horizon mode à Sources of randomness
ÓShip residual capacity for taking empty containers
(given port and time period)
ÓDemand for containers at each port/time
Formulation
(2)à Minimize total expected (cost – revenue from demand) à Ship container conservation: containers unloaded
à Ship container conservation: containers loaded for
repositioning
à Port container conservation / demand satisfaction à Ship residual capacity for repositioning
Plan
à What are we talking about?
à Brief overview of freight transportation à Container-based intermodal transportation à System design (location)
à Fleet Management (empties)
Perspectives
à Intermodal transportation
ÓGrowing steadily & should continue to grow ÓContainers and other modes
à Profound modifications to the economic, regulatory,
technological, social and political environment of industry
à Globalization, automation, ITS, e-logistics, security, … à Need for innovative and enhanced planning and
management procedures
à Opportunities for Operations Research and
Perspectives
(2)à A number of research efforts and important results
à Much more work is needed!
à Many issues application areas not/little addressed à Industry evolution ⇒ New problems
à Ports & terminals
ÓPlanning (all levels)
ÓIntegration of operations & equipment types ÓAutomation
Perspectives
(3)à Carrier strategic & tactical planning ÓMore studied than terminals, but
ÓBetter representation/integration of “local” operations
and characteristics
ÓIntegration of employee scheduling impacts/relations ÓBetter representation of time dependencies
ÓBetter integration of stochastic aspects into long-term
planning models
Perspectives
(4)à Short-term planning
ÓTime-dependent, stochastic formulations and
algorithms
ÓIntegrated models, e.g.,
IContainer fleet management over land and sea IVehicles, power, crews, …
à Modelling of ITS and e-logistics and integration to
planning and management models; e.g.,
ÓFlow of information
Perspectives
(5)à Modelling the impact of security measures and
addressing the new issues
à Logistic networks
ÓCoordination & synchronization
ÓInformation flows and uncertainties à Methodology
ÓModels
ÓMethods exact and (meta) heuristic ÓParallel computation
