Intermodal Transportation

Transcription

1 Intermodal Transportation Teodor Gabriel Crainic ESG UQAM & CIRRELT - CRT CIRRELT

2 Plan What are we talking about? Container-based intermodal transportation System design (location) Fleet Management (empties) Perspectives 2

3 What are we talking about? 3

4 Intermodal Transportation Simple and straightforward definition: 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 E.g., Door-to-door transportation of containers Over long distances Origin land transport port container ship port land transport destination 4

5 A Strict Definition Movement of goods One and the same loading unit or vehicle A chain of Several transportation modes (services) Coordination Interactions Intermodal terminals No handling of the goods themselves Door-to-door service European Conference of Ministers of Transport (1993) 5

6 A More General Definition Movement of goods A chain (network) Several transportation modes (services) Coordination (more or less) Interactions Intermodal terminals Door-to-door service 6

7 Many Things to Many People Major instrument for E.U. policy aimed at switching freight from trucks & highways to more environmentfriendly modes (rail, water) Dedicated rail services (subdivisions) to move large volumes of containers/trailers over long distances: the trans-continental land bridges Container transportation Consolidation carriers: local & long-haul operations, several long-haul types of services, with/without use of external services 7

8 Many Things to Many People (2) Uncontainerized cargo Courier (express) services National planning City Logistics Terminal (ports, airports, ) planning and operations 8

9 Scope of Presentation Container-based intermodal transportation Illustrative planning/operations management issues Operations research models and methods A very young field No definite answers An open invitation to join in!! 9

11 Intermodal Transportation Containers Advantages Reduced cargo handling Increased security regarding damage and loss Increased standardization of transportation and transfer equipment Increased automation of terminal operations Cost reduction, more efficient door-to-door transportation Sustained growth 11

12 Evolution of Container Traffic (Koh and Kim 2001) Year Container traffic (M) Growth rate (%)

13 Intermodal Transportation Containers (2) Lifeline of world-wide trade and economy Increasingly larger container ships for inter-continental transportation (liners) These cannot berth at all ports It is not economical to stop at many ports Container mega ports New coastal navigation feeder services ( regular ships): mega ports and huge liners regular ports A new link in the multi-modal chain New long-distance rail services (double-stack) 13

14 Intermodal Transportation Containers (3) Asia (Hong Kong, Singapore, ) to America or Europe: Origin truck port large container ship (liner) mega port small container vessel port truck/rail/river destination Container port terminal transformations for increased efficiency in loading/unloading operations and exchanges with land carriers New terminals / Enhancement of existing ones Automation Intelligent Transportation Systems 14

15 Notes Container intermodal transportation (& express courier / post services) Customer: Customized service Operator(s): Hub-and-spoke network with consolidation All long-haul transportation must address the issue of empty vehicle repositioning Trade is unbalanced Vehicle flows as well!! Tight fleet size? Long distances? 15

17 System and Service Design Strategic decisions System Design Locate (intermodal) terminals Direct/indirect customer (zone) service Port/terminal dimensioning Number of berths Size of storage space Type & number of various equipment types Facility & service abandon, 17

18 System and Service Design (2) Tactical decisions Service Design Routes served (routes, stops, mode, equipment, ) Service frequency & schedule Cargo routing Terminal workloads Container port terminal equipment assignment To sea-side and land-side operations Not many contributions for container transportation 18

19 System Design Not many contributions Tactical or operational models to evaluate strategic strategies Ports: queuing, simulation Discrete location models Consolidation / hub terminals Network design + location Select direct services/links Aim to capture economies of scale associated to consolidation of freight 19

20 System Design (2) Location of facilities (terminals) Production-distribution Hub location Location with balancing requirements 20

21 Location with Balancing Requirements Land part of an intermodal container transportation system (may be generalized) Use in-land container depots for more efficient operations and reduced empty travel 21

22 Traditional Operations Loaded Empty Importing customer Exporting customer 22

23 Operations with In-Land Depots Loaded Empty Empty balancing Importing customer Exporting customer 23

24 Location with Balancing Requirements (2) Loaded movements are profitable Empty movements are not Customer to depot: Return movement Supply of empties Depot to customer: Demand satisfaction Demand for empties Depot to depot: Repositioning of empty containers due to unbalances in supply/demand 24

25 Location with Balancing Requirements Network O i supply O ip i customers c ijp j s jkp k depots i' demand D ip customers D i' 25

26 O i supply i customers y j x ijp j w jkp k depots i' x ki ' p demand customers D i' (flows of empty containers) 26

27 Location with Balancing Formulation Minimise Z = j D f y j j + { ( c x + c x ) + s w } p P i C j D ijp ijp jip jip jkp jkp j Dk D Subject to j D j D x = O i C, p P ijp ip x = D i C, p P jip ip [Demand / Flow conservation] 27

28 Location with Balancing Formulation (2) x Oy i C, j D, p P ijp ip j x D y i C, j D, p P jip ip j [Linking / Feasibility] x + w x w = 0 j D, p P ijp kjp jip i C k D i C k D [Balancing] x, x 0 i C, j D, p P ijp w 0 j D, k D, p P y jip jkp j jkp {,} 0 1 j D 28

29 Plan What are we talking about? Brief overview of freight transportation Container-based intermodal transportation System design (location) Fleet Management (empties) Perspectives 29

30 Operational Planning Resource management Crews Vehicles Power (engines, etc.), and so on Allocation dispatching, schedules Make sure the required resources are where they need to be when they need to be there Be efficient! (Satisfy demand, achieve economic and service objectives, implement plan, obey laws, policies, ) 30

31 Issues Trade is unbalanced Moving goods results in unbalanced distribution of resources: crews, vehicles, etc. One needs to reposition resources for use in the following periods Regular operations (if possible) Balancing operations (vehicles, power units, ) Crews travelling as passengers The demand in following periods is a forecast 31

32 Other Operational Issues Real-time dispatch Pacing Real-time routing adjustment 32

33 Consolidation Transportation Transportation plan guides operations It includes guidelines for repositioning (it should ) Indicative schedules: Ad-hoc (real-time) procedures Regular demand planning: Short-term and real-time adjustment of plans Scheduled operations: Repositioning must follow and feed schedules + real-time adjustment Well-defined crew (personnel) schedules 33

34 Customized Transportation No plan!! Dynamic management and control of resources: routes, schedules, fleets, personnel, etc. Uncertainty plays important role Demand Travel times Service times at customers and terminals Weather, 34

35 The Empty Vehicle Repositioning Problem Surpluses and deficits of empty vehicles Observed at terminals at the end of the day Computed with respect to the next period demand Need to reposition for the next period How many vehicles (of what type) to move from a surplus location (origin) to a deficit location (destination)? Much more decision freedom than in loaded transportation A cost activity with no profit 35

36 History Transportation model static and deterministic Known surpluses and deficits No uncertainties No (not important) travel time impact Static Arrival times known (certain prediction) All travel, loaded and empty, occurs during the same period Single or fully substituable resources (vehicles) For certain LTL types, tactical planning, 36

37 History (2) Deterministic, multi-period transshipment model Different movements require different travel times Vehicles become empty at different moments (customer release times) Demand varies in time The dynamic characteristic of the system represented through (dynamic, time-dependent) space-time networks 37

38 Space-Time Networks Nodes: Facilities terminals, customers, etc. at given time periods A physical point is repeated at each period & activity Arcs: Movements in space and time Independent, e.g., a truck moving by itself Grouped, e.g., containers on flat cars (rail) or in a ship Holding decisions (vehicles or cargo) 38

39 Space-Time Network (Simple) Time Terminals Current period Inventory (holding) arc Repositioning arc Future periods 39

40 Space-Time Network Time Terminals Current period Inventory (holding) arc Repositioning arc Future periods 40 Loaded movement End of horizon

41 Challenges and Limitations One may include Capacities Several types of resources Inventory costs Stock out (rent, borrow, ) End of horizon value Substitutions (and costs) Complex cost structures Linear programming formulations with a few complications 41

42 Challenges and Limitations (2) Planning horizon length? End-of-horizon? Rolling horizon Everything is deterministic Times (travel, terminal operations, customer, ) Future demand, etc. Utilization Strictly scheduled railways with bookings 42

43 The Uncertainty Factor Times may vary Demand estimation is rarely precise Unexpected demands and events Current decisions impact the future state of the system and future decisions Need to explicitly consider / model Uncertainty the stochastic nature of the system and its environment The impact of current decisions on future system state and decisions 43

44 The Uncertainty Factor (2) Stochastic formulations and solution methods A complex field: General approaches and, often, custom-designed methods Active research field Formulations General stochastic programming and solution methods : Few efficient applications to transport problems 44

45 The Uncertainty Factor (3) Formulations Recourse formulations and rolling horizon methods Nice application to regular-type systems (e.g., consolidation) Stochastic formulation and solution strategies based on adaptive dynamic (linear) programming and decision/time-based decomposition Time-Space multicommodity networks Recent developments with interesting results 45

46 The Uncertainty Factor (4) Challenges of stochastic formulations Problem formulation (!!) Resolution (!!) Plus Representation of resources and attributes Forecasts Availability and reliability of data Validation of models and strategies Implementation and follow up 46

47 Container (Empty) Fleet Management Major repositioning decisions over large geographical regions (e.g., inter-continental movements) Similar to consolidation transportation Allocation of empty containers to customers Similar to customized transportation Two applications in this talk Allocation and management of a heterogeneous fleet of containers over a land zone Single-commodity dynamic container allocation for liner operators (regular ocean navigation lines) 47

48 Heterogeneous Fleet Given region (continent) Loaded containers arrive (e.g., maritime network) to be delivered to customers Empty containers arrive or leave to balance system-wide operations (demand) Customers empty containers that must be moved out Customers require empty containers for future loaded shipments One must manage the fleet of containers for maximum profit, while satisfying demand 48

49 Heterogeneous Fleet (2) Several types of containers (e.g., 20 or 40 feet, normal box, thermal, refrigerated, etc.) Substitutions allowed: conditions and costs Massive inter-depot balancing movements Due-dates at some terminals (e.g., ship schedules) Time windows at customers Demand (at least part of) fluctuates in time and is forecasted only Unloading time at customer: Uncertain Travel times may be uncertain as well 49

50 Heterogeneous Fleet (3) Containers may be damaged partially (repairs) or totally External sources (buy, rent) of empty containers Centralized empty container fleet management Loaded movements not managed Associated problem: global management of the empty & loaded container movements together with vehicle routes A single model not computationally feasible hierarchical DSS 50

51 Main Movements (No Time/Container Type Specifics) Harbour Depot j Demand customer Supply customer Depot k External pool of empty containers 51

52 Formulations Crainic, Dejax, Gendreau (93) Single and multicommodity deterministic formulations A two-stage, restricted recourse single commodity, stochastic model Multicommodity stochastic formulations may be defined 52

53 Formulations (2) Space-time diagram Generalized network (substitutions) Multiple-period transportation arcs Holding arcs (depots) Inter-depot balancing arcs Stochastic elements Demand (of known and possible customers) Release time from supply customers Inventory levels Import and export (border points, external pool) 53

54 Formulations (3) Minimize total cost over the time horizon Flow conservation (over time and space, including access to external pool) Supply at supply customers Demand Container substitution Depot (and port) inventories (each container type) Bounds on inter-depot balancing flows End-of-horizon restrictions (e.g., limits on final inventories) 54

55 Single Commodity Liner Cheung and Chen 1998 A container liner company offers regular service among a number of ports Carries loaded and, space permitting, empty containers Ship schedules known and fixed 1 ship / period between 2 ports Demand less than ship capacity 1 container type 55

56 Formulation Two-stage stochastic model Time-space network with random arc capacities Minimize the (expected) total cost Rolling-horizon mode Sources of randomness Ship residual capacity for taking empty containers (given port and time period) Demand for containers at each port/time Supply of containers at each port /time before unloading from ships 56

57 Formulation (2) Minimize total expected (cost revenue from demand) Ship container conservation: containers unloaded Ship container conservation: containers loaded for repositioning Port container conservation / demand satisfaction Ship residual capacity for repositioning Number of leased containers 57

58 Plan What are we talking about? Brief overview of freight transportation Container-based intermodal transportation System design (location) Fleet Management (empties) Perspectives 58

59 Perspectives Intermodal transportation Growing steadily & should continue to grow Containers and other modes Profound modifications to the economic, regulatory, technological, social and political environment of industry Globalization, automation, ITS, e-logistics, security, Need for innovative and enhanced planning and management procedures Opportunities for Operations Research and Transportation Science 59

60 Perspectives (2) A number of research efforts and important results Much more work is needed! Many issues application areas not/little addressed Industry evolution New problems Ports & terminals Planning (all levels) Integration of operations & equipment types Automation 60

61 Perspectives (3) Carrier strategic & tactical planning More studied than terminals, but Better representation/integration of local operations and characteristics Integration of employee scheduling impacts/relations Better representation of time dependencies Better integration of stochastic aspects into long-term planning models Algorithmic developments 61

62 Perspectives (4) Short-term planning Time-dependent, stochastic formulations and algorithms Integrated models, e.g., Container fleet management over land and sea Vehicles, power, crews, Modelling of ITS and e-logistics and integration to planning and management models; e.g., Flow of information Impact on uncertainty 62

63 Perspectives (5) Modelling the impact of security measures and addressing the new issues Logistic networks Coordination & synchronization Information flows and uncertainties Methodology Models Methods exact and (meta) heuristic Parallel computation 63