Service Network Design for Consolidation Freight Carriers

Transcription

1 Service Network Design for Consolidation Freight Carriers Teodor Gabriel Crainic ESG UQAM & CIRRELT - CRT CIRRELT

2 Consolidation Freight Transportation Long distance freight transportation Railways Less-Than-Truckload (LTL) motor carriers Shipping lines Container transportation Postal and express couriers: Service (firm) planning perspective Regulatory agencies (in some countries) 2

3 2 Terminal b d e 1 3 a c f Customers 4 A 5 B 6 Hub 7 C Main Feeder Pick up and delivery

4 Consolidation Transportation (2) The same vehicle (convoy) serves the demand of several customers Regular services Routes, frequencies, schedules Terminals: Major and central role Sort freight and consolidate it into vehicles Sort vehicles and group them into convoys Manipulate convoys Many types of services, equipment, and terminals Many trade-offs among operations and among performance measures 4

5 Consolidation Transportation (3) Reduces costs for customers Reduces costs for carrier (if correctly planned and performed) Reduces the flexibility of customers Additional operations and delays (in terminals) Reduced reliability (and costs) Operation efficiency Carrier profitability Service quality (delays, reliability, ) Customer satisfaction Need for methods to plan and manage operations 5

6 Tactical Planning Objectives Determine the best optimal assignment and utilization of resources to fulfil the economic and service (customers) objectives of the carrier Means Tactical (load, transportation, ) plan Yields Operation plan for normal/regular operations Scenario analysis tool 6

7 Vocabulary Physical network Infrastructure network on which transport services operate Rail tracks and stations Public roads and terminals (motor carriers, post, express mail, ) Airports, ports, LTL breakbulk and end-of-line terminals, intermodal terminals in general, Conceptual air, sea, river, connections 7

8 Physical Network terminal A terminal B terminal C terminal D terminal F terminal E 8

9 Vocabulary Transport Services For the customers Point-to-point (city-to-city, origin to destination) service offer Frequencies and schedules Tariffs Service targets: Paris to Frankfurt in 24 hours For the carrier Origin (terminal), destination (terminal), route through the physical network, stops, equipment type, 9

10 Services terminal A terminal B S3 S4 terminal C Modes S1 S2 S5 terminal D S7 S5 terminal F terminal E S6 10

11 Transport Services Carrier Operations costs Frequencies and schedules Service targets: Paris to Frankfurt in 24 hours, 80% of the time The origin and destination as seen by a customer are generally not those of a carrier service Pick up and delivery Freight moved by a series of transport services and terminals Terminals = services 11

12 Vocabulary Demand Market = Traffic class Origin, destination, product Quantity Priority level delay cost Routing - Itineraries Origin, destination, route through service network Terminal operations Quantity and performance measures 12

13 Itineraries : A to E terminal A S3 S4 terminal B Modes terminal C (A, E) S1 S2 S5 terminal D S7 S5 terminal F terminal E S6 13

14 Itineraries : A to E (2) terminal A S1 S2 terminal E (A, E) S4 S3 terminal D S6 S5 terminal C S5 S7 terminal B terminal F Modes 14

15 Itineraries : A to E (3) terminal A (A, E) S3 S4 terminal B Modes terminal C S1 S2 terminal E (A, E) terminal D S6 S5 (A, E) S7 S5 terminal F Transfer at C from S3 to S5 Transfer at D from S5 to S6 15

16 Itineraries : A to E (4) terminal A (A, E) S3 S4 terminal B Modes terminal C S1 S2 terminal E (A, E) terminal D S6 S5 (A, E) S7 S5 terminal F Transfer at C from S3 to S5 Consolidation at D from S5 to S6 16

17 Itineraries : Extra A to E + B to F (A, E) terminal A S1 S2 terminal E (A, E) (A, E) S3 terminal D S6 terminal C S5 S7 terminal B S4 (B, F) S5 (B, F) et (A,E)+ terminal F Modes (B, F) 17

18 Best Itinerary (there are quite a lot of them)? It depends The state of the entire system Moving the entire demand Congestion in (in front of) terminals (lines) Frequency and utilization (loads) of services The trade-off between operation costs (to minimize) and the service quality (to maximize) Need to optimize the entire set of operations in an integrated way 18

19 (in 1000$) Handling and transportation costs Company performance 42% 87% $ 490 Model results % $ $ No. of markets that satisfy quality requirements (%)

20 Interrelated Decisions Service selection Routes, types, frequencies, schedules, Freight routing (distribution) Itineraries (routes), volumes, Empty vehicles Terminal utilization policies Work division Network-wide interactions and trade-offs Among components/operations/decisions Between cost and quality objectives 20

21 Decision Environment Interactions occur network-wide ( ripple effect ) The impact of individual decisions are difficult to forecast and rarely intuitive Trade offs are difficult to identify 21

22 Service Network Design Construction of tactical plan Aggregated modelling of the major system components, decisions, operations Planning, not operations Integrates trade-offs costs versus service quality Interactions of several types of resources Network-wide level 22

23 Service Network Design (2) Planning horizon Strategic/tactic Tactic/operational Service network design model (methodology) Static Dynamic (time-dependent) Deterministic (why not stochastic?) Model objective Static: Selection & Frequencies Dynamic: Schedules (& dispatching) 23

24 Static Service Network Design Objectives Strategic/tactic planning Transportation plan Interaction and trade-off analyses Scenario analyses Typical issues Do we operate the service? How often over the planning horizon? What service type? Terminal loads? Itineraries for demand and empty vehicles? 24

25 Static Service Network Design: Approches Selection of services Frequencies as Consequences of routing decisions (Powell et al) Decisions (Crainic et al) In all cases, the service network represents the decision structure on which traffic routing decisions are taken 25

26 Selecting Services Decisions To operate or not each service: {0,1} variables Demand routing: continuous flow variables Demand for several Products (appropriate measures: tons, # of vehicles, ) Each service Fixed cost to operate Variable cost to transport products Capacity 26

27 Selecting Services (2) y x u S 1 s AE s 1 1 terminal A S1 S3 d AE, d AF, d AD S2 y x u s s AE s S3 y x x x u SAE 3 SAF 3 SAD S 3 3 S5 terminal D S4 terminal C S5 S7 terminal B terminal F Modes terminal E S6 27

28 Selecting Services: Modelling Network Nodes: Terminals Links = services Decisions i, j T a= (, i j) S;, i j T Is a service a, from terminal i to terminal j, to be selected (operated, offered)? y {1, 0} Quantity of demand of market od carried on service a xaod 0 a 28

29 Selecting Services: Formulation Minimize Subject to p s s s sp s S p P s S sji s S j s S j p P y x s sp fy x x sp s s {0,1} 0 + u y Cx d p if at origin x = sij 0 if other terminal dp if at destination Flow conservation Linking/ capacity 29

30 Service Network Design Fixed-cost, capacitated, multicommodity, network design formulations (arc or path) Combinatorial and difficult Additional constraints from operational considerations Solved by Exact methods (B&B, ) for small instances Heuristics and Meta-heuristics in most cases Frequency formulations (general integer design variables): even more complex 30

31 Frequencies as Decisions Applications to railways, LTL motor carriers, courier, etc. Determine service frequencies Routing of demand for each market Service and terminal work charges derived from frequencies and itineraries More complex service routes Service and terminals capacity and congestion Minimize the generalized cost of operating costs, service quality measures, delay costs, etc. Non linear formulation due to frequency/congestion impact 31

32 Modelling Service Network Set of services S Defined on the physical network Each service s S : origin, destination, route, stops, type, capacity, Service frequency y s integer (=0,1,2,3, ) Select frequencies Determine services to be offered and the level of service Fixed cost to operate each occurrence of a service Ψ s ( y) May depend upon the frequencies of all services 32

33 Modelling Demand Itineraries Defined on the service network p Several itineraries l L may exist and be used for each market p P Itinerary : origin, destination, service route, operations at terminals, Quantity of demand of market p moved by itinerary l p (continuous) hl 0 p Variable cost to move along each itinerary Φ l ( yh, ) May depend upon the service frequencies and the volumes moved on the other itineraries 33

34 Congestion Phenomena: Average Delays When several services / itineraries use the same facility, there is competition for the same resources Congestion Non linear relations between facility capacity (time to go through it) and the volume that needs to use it: a small increase in volume results in a large increase in average utilization time Congestion functions 34

35 Delays and Congestion Average delay (time) = free travel time * [ total traffic (total traffic / capacity) 6 ] Capacity Total traffic 35

36 Operations with Congestion Single and double rail lines: meets and overtakes Congested roads Car classification, block and train make up (rail yards) Connection: waiting for the next service (terminals) Truck waiting at terminal doors Ship waiting at port or lock entry Freight classification and consolidation (terminals) Vehicle loading/unloading, Functions are derived from engineering and queuing formulas, through simulation 36

37 Modelling Capacity Restrictions For modelling & algorithmic reasons, capacity restrictions and other service quality measures are better represented as non-linear penalties in the objective Hard constraints in actual operation Hard capacity constraints: more difficult design problem Overcapacity corresponds to longer delays The model should be able to go over capacity and pay the price if it yields a better overall performance The possibility to explore strategies and tradeoffs that strict constraints do not allow to see 37

38 Capacities as Penalties Total volume on segment k (between two consecutive stops) of service s with current frequency y s = Sum of the volumes of all itineraries using segment k of service s x sk Service capacity on segment (minimum of the capacities of the links making up the segment) u sk Penalty cost for overloading the service s P C s Θ = ( yh, ) C P min{0, u y x } ( ) 2 p l s s k sk s sk 38

39 Service Costs Fixed Cost to operate one occurrence of the service Sum of unit operating costs on the lines and in the terminals of its route Service travel time Τ s Average (expected value) E[ Τ s ] Sum of [average] travel times and terminal handling times D Cost of handling and travel time C s Service total cost O D Ψ ( y) = ( C + C E[ Τ ]) y s s s s s O C s 39

40 Itinerary Costs Variable Cost to use itinerary l for market p O C lp Sum of unit operating cost on the lines (services) and in the terminals of the itinerary p Itinerary travel time Τ l ( yh, ) p Average (expected value) E[ Τl ( yh, )] Sum of service travel times and terminal handling times D C lp Cost of travel and wait (delay) Itinerary total cost Φ ( yh, ) = ( C + C E[ Τ ( yh, )]) h p O D p p l lp lp l l 40

41 Operation Costs Generally linear (proportional) with traffic volume Operate engines or trucks Hauling full and empty vehicles Sort and consolidate freight Load / unload vehicles (trucks, wagons, barges, ) Sort wagons Build blocks and make up trains Transfer blocks (wagons) between trains 41

42 Time costs Unit time costs Depreciation, crews, product value, priorities (how urgent it is to deliver a product), etc. Transform time into money coherent objective function 42

43 Delays Total travel time, origin to destination, serves as servicequality indicator for services and itineraries Sum of travel times (delays) and terminal handling times (delays) making up the service / itinerary Often, constant average time values Roads, maritime transport, Load / unload / transfer vehicles, Non linear when congestion phenomena exist 43

44 Averages Do NOT Tell the Whole Story Service reliability or fulfilment of targets are not well represented through average delays Penalize ( large ) variances Introduce variances into the computation of total time and penalize not respecting targets Announced target (e.g., 24 jour delivery) H p Target (e.g. 90% of occurrences) n D p p p C h (min{0, H E[ Τ ( y, h)] nσ [ Τ ( y, h)]}) lp l p l l 2 44

45 Frequencies as Decisions Decisions Service frequencies (integer) Routing itineraries of demand for each market (continuous) Objective: Generalized cost of operating costs, service quality measures, delay costs, etc. Non linear formulation due to frequency impact (congestion) Path-based formulation 45

46 Model Idea Minimize total generalized system cost = Fixed cost to offer the service + Variable costs to operate full and empty vehicles Constraints Satisfy demand for each market (other operational considerations) Operational policies (e.g., capacities of vehicles, convoys, lines, terminals, ) and service targets are in the objective function 46

47 Formulation Minimize Subject to ss l L y h s p l Ψ () y + Φ (,) y h +Θ(,) y h p h s p l 0 and integer 0 = w pp p l L p p l + Particular operational constraints 47

48 Solving the Model Heuristics (modify frequencies) and exact methods (itinerary generation and flow distribution) Better methods have been developed (for the generic model; work in progress ) Applications Many models in the literature use the same approach with simplifications 48

49 Service Network Design Static: Selection and frequencies Dynamic: Schedules and dispatching When will the service leave? (If it does ) Moving the freight Repositioning of resources (vehicles, crews, motor power) 49

50 Space-Time Network (Diagram) Representation tool for time-dependent events (demand, activities, decisions, ) and their relations in time and space The network describes the system operations during the current and the following time periods Arcs represent inter-period relations (inventories, movements, etc.) The objective function minimizes/maximizes the total cost/profit over the entire multi-period planning horizon 50

51 Space-Time Network Schedules Time Terminals Period t Possible departure Period t + 1 Periods t + 51 Inventory arc End of horizon

52 Space-Time Network Cyclic Schedules 52

53 Modelling Idea Physical network represented at each period Arcs represent each possible departure (origins, intermediary stations) of each service Waiting/holding (inventory) arcs link nodes representing the same terminals in consecutive periods Decision variables {0,1} : The corresponding service leaves (is operated) at the specified time? Continuous: Freight flows 53

54 Modelling Idea (2) Modelling principles and components of the static formulations apply Problem dimensions grow fast!! Network design solution approaches Adaptations of fleet management (dynamic resource allocation) methodologies There is a lot of work required in this field!! 54

55 An Example of New Challenges Dedicated intermodal rail services to move containers & trailers Instrument for E.U. policy Consolidation carriers with/without external services Efficiency and profitability of operations Same ideas apply to the planning of services of regular navigation lines Old issues, new operation principles, new challenges 55

56 Rail Intermodal Dedicated carriers (divisions) North America Long distances land bridges linking the coast and the industrial mid-west Long trains (very long ) Double stack Scheduled services (almost) Bookings and full-asset-utilization operations (emerging) 56

57 Rail Intermodal (2) Europe Separation of infrastructure owners/managers (capacity providers) and operators (service providers) Scheduled services: network is congested!! Double stack (where possible) Bookings (contemplated) New services Shuttle services E.U. expansion to Central and East Europe 57

58 Rail Intermodal Trends Full asset utilization operations Same trains & blocks operated every day, all days (seasonal) Equipment engines & cars and personnel operates circular routes Bookings Advance reservation of space (slot) on train/day Advanced terminals on the drawing boards Intelligent systems 58

59 Rail Intermodal New Networks in Europe Expansion of EU German network very congested New shuttle networks Link Scandinavia to Central Europe and beyond Use uncongested Eastern rail networks: Polish, Czech, Andersen, Christiansen, Crainic 05 59

60 The Polcorridor project Northern feeder network SWINOUJSCIE SZCZECIN GDYNIA GDANSK Hubs VIENNA Southern feeder network 60

61 The System Swinoujscie/ Szczecin Gdansk/ Gdynia Poznan Zielona Góra Wroclaw Miedzylesie Chalupki Node in rail network Intermodal hub Border crossing node Vienna Breclav Rail lines Czech/Polish border with change of locomotive Node in external network External service 61

62 Swinoujscie Rail-Ferry Terminal Representation Arrival of ferry Quay Unloading of containers& semitrailers Storage area Transhipment of rail wagons Loading of containers& semitrailers Rail terminal Locomotives ready for new departure TRAIN DEPARTURE Departure of ferry Quay Loading of containers& semitrailers Storage area Transhipment of rail wagons Unloading of containers& semitrailers Rail terminal TRAIN ARRIVAL 62

63 Two Models Strategic/tactical for major design decisions Services: types, routes, frequencies Market selection (some pricing issues) and routing Frequency service network design Service & schedule planning When service depart given ideal frequencies Coordination and synchronization External networks (ferries, other rail services) Multi-carriers & border crossings 63

64 Common Characteristics and Issues Cyclic schedules Cyclic Space-Time Network Representation t=1 t=2 t=3 t=4 t=5 t=6 Node 1 Node 2 Node 3 64

65 Common Characteristics and Issues (2) Need to include locomotive management Repositioning Circular routes Change of locomotive at the Czech Polish border Need to synchronize/coordinate 65

66 Scheduled Service Design + Asset Management + External Service Coordination (Model 2) Time-space representation with repetitive service network Border crossings with synchronization Design new services interacting with existing/external services Some departure times are fixed Balancing of assets (locomotives) at nodes Repositioning allowed to create feasible locomotive (circular) movements 66

67 Model Minimize total time cost : travel + waiting for various terminal operations (border, connection, ) The fleet of locomotives must cover all services and repositioning in each time period Node asset (locomotive) balance Lower and upper bounds on service frequencies Node freight (rail car) balance Train capacity on internal and external services 67

68 Design-Balanced Network Design At the core a new variant of multicommodity capacitated network design problem Design balance constraints The number of selected design arcs entering a node = number of selected design arcs exiting the node 68

69 Arc Formulation (DBCMND) min zxy (, ) = fy+ cx p p ij ij ij ij (, i j) A p P (, i j) A p w if i = o( p) x x = d = w if i= s( p) i N, p P 0 otherwise p x u y (, i j) A p p p p ij ji i + j N () i j N () i p P ij ij ij y y = 0, i N ij + j N () i j N () i p ij x 0 ( i, j) A, p A y N ( i, j) A ij ji 69

70 Design-Balanced Network Design Exact solution methods work on very small instances Heuristic methods for particular cases LP relaxation & column generation + cuts + rounding Path-based generate + combine to improve Arc-based general formulation Tabu search-based method yields promising results Interesting cycle-based formulation has been proposed 70

71 Methodological Challenges Advance network design methodology Transfer methodology to application areas Time-dependent design-balanced service network design Formulations & characterization Efficient solution methods, Stochastics and service network design Preliminary studies: plans are different and better... Requires work on realistic formulations & efficient solution methods 71