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Vehicle Circulation and the Hungarian Method. Martin Grötschel joint work with Ralf Borndörfer Andreas Löbel Celebration Day of the 50th Anniversary of the Hungarian Method Budapest, October 31, 2005. About the assignment problem.

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Vehicle circulation and the hungarian method l.jpg

Vehicle Circulation andthe Hungarian Method

Martin Grötschel

joint work with

Ralf Borndörfer Andreas Löbel

Celebration Day of the 50th Anniversary of the Hungarian MethodBudapest, October 31, 2005


About the assignment problem l.jpg
About the assignment problem

  • The assignment problem is a mathematical problem. Mathematicians have spent an awful lot of time to create “real-life interpretations” that look like applications to “prove” that it is useful. And hence, the Hungarian Method is of no practical value.

  • The “truth”, in fact is the other way around. Practitioners have “tuned” their applied problems in order to be able to employ the Hungarian Method.

Martin Grötschel


Contents l.jpg
Contents

  • What is vehicle circulation/scheduling?

  • Single depot vehicle scheduling

  • Multiple depot vehicle scheduling

  • Extensions

Martin Grötschel


Contents4 l.jpg
Contents

  • What is vehicle circulation/scheduling?

  • Single depot vehicle scheduling

  • Multiple depot vehicle scheduling

  • Extensions

Martin Grötschel



The zib transportation team including former members l.jpg
The ZIB Transportation Team,including former members:

Public Transport:

Ralf BorndörferFridolin KlostermeierChristian KüttnerAndreas LöbelSascha LukacMarc PfetschThomas SchlechteSteffen Weider

Online Transportation:

Norbert AscheuerPhilipp FrieseSven O. KrumkeDiana PoensgenJörg RambauLuis Miguel TorresAndreas TuchschererTjark Vredeveld

plus several master students

Martin Grötschel


Planning in public transport product project planned l.jpg

Cost Recovery

Fares

Construction Costs

Network Topology

Velocities

Lines

Service Level

Frequencies

Connections

Timetable

Sensitivity

Rotations

Relief Points

Duties

Duty Mix

Rostering

Fairness

Crew Assignment

Disruptions

Operations Control

Planning in Public Transport(Product, Project, Planned)

multidepartmental

Departments

multidepotwise

Depots

multiple line groups

Line Groups

multiple lines

Lines

multiple rotations

Rotations

VS-OPT2

B15

IS-OPT

Martin Grötschel

APD

DS-OPT

VS-OPT

BS-OPT

AN-OPT

B1

B3

B1


The zib transportation team spin off companies l.jpg
The ZIB Transportation Teamspin-off companies

Intranetz:

Fridolin Klostermeier

Christian Küttner

Norbert Ascheuer

LBW:

Ralf Borndörfer

Andreas Löbel

Steffen Weider

Martin Grötschel


What is vehicle circulation scheduling l.jpg
What is vehicle circulation/scheduling?

  • We are given a transportation system in a region.

  • It is subdivided by carrier/vehicle types (busses, trams, subways, planes, ships…).

  • For each carrier type, a (daily, weekly, or monthly,..) timetable (the scheduled/timetabled trips) is given.

  • Task: Assign the available vehicles to the scheduled trips of the timetable such that some objective function is optimized and a (usually large) system of side constraints is satisfied.

Martin Grötschel


What is vehicle circulation scheduling somewhat more precise l.jpg
What is vehicle circulation/scheduling?Somewhat more precise:

  • Each vehicle (usually) has a home base. In colloquial language this is called its depot. Transportation professionals have to be more precise. A depot consists of all indistinguishable vehicles that have their home base in the same physical location.

  • In most cases, a vehicle leaves its depot in the “morning” and returns to its depot in the “evening” of the planning period. Thus, every vehicle “circulates” along a tour of the region.

  • The vehicle circulation problem is hence the task to find, for each available vehicle and for the given planning horizon, a tour such that all scheduled/timetabled trips are covered by exactly one tour and some objective is optimized and certain side constraints respected.

Martin Grötschel


What is vehicle circulation scheduling the objective function l.jpg
What is vehicle circulation/scheduling?The objective function

  • Minimize the number of vehicles that are necessary to cover all scheduled trips.

  • Minimize the cost of the deadhead trips.(Deadhead trips are moves of a vehicle without passengers; a move can be just a break where the vehicle keeps waiting in a parking lot.)

  • A combination of these two.

  • Interlining

  • Turns

  • Pull-in pull-out trips

Martin Grötschel


Slide12 l.jpg
Leuthardt Survey(Leuthardt 1998, Kostenstrukturen von Stadt-, Überland- und Reisebussen, DER NAHVERKEHR 6/98, pp. 19-23.)

annual cost: 150 – 250 thousand US dollars per bus

Martin Grötschel


Vehicle scheduling in berlin l.jpg
Vehicle Scheduling in Berlin

The transportation research group at ZIB has produced software with which the

  • busses

  • street cars, and

  • subways

    in Berlin have been scheduled.

    A film shows some of the problems of bus scheduling:

Martin Grötschel


Vihicle circulation film l.jpg
Vihicle Circulation Film

Martin Grötschel


Some users l.jpg
Some Users

Martin Grötschel


Contents16 l.jpg
Contents

  • What is vehicle circulation/scheduling?

  • Single depot vehicle scheduling

  • Multiple depot vehicle scheduling

  • Extensions

Martin Grötschel


Single depot vehicle scheduling assignment model l.jpg
Single Depot Vehicle Scheduling(Assignment Model)

depot (in the morning)

D

D

1

2

1

2

with starting time and location

timetabled trip

1

1

2

2

with ending time and location

4 timetabled trips

4

4

3

3

  • A single depot:

  • one location

  • one bus type

3

3

4

4

depot (in the evening)

D

D

Martin Grötschel


Single depot vehicle scheduling assignment model18 l.jpg
Single Depot Vehicle Scheduling(Assignment Model)

D

1

D

D

2

3

D

4

1

2

1

2

3

D

D

1

2

4

1

1

2

2

D

1

D

2

3

4

D

1

D

2

3

4

4

4

3

3

3

3

3

D

D

1

2

4

4

4

3

D

D

1

2

4

D

D

4 timetabled trips plus

12 deadhead trips

1 blue and 1 red

bus circulation

2 depot nodes foreach available bus

The assignment model of thesingle depot vehicle circulation problem

Martin Grötschel


Slide19 l.jpg
But

  • In the seventies the available computers were not able to solve large size assignment problems due to time and space problems.

  • The Hungarian method was the algorithm of choice. There was nothing better.

Martin Grötschel


Problem specific size reduction hot hamburger optimierungstechnik l.jpg
Problem Specific Size Reduction:HOT = Hamburger OptimierungsTechnik

HOT only looked atpeak times (about 7 a.m) and made heuristic (manual = interactive) choices toreduce the problem size.

~ 1975 beginning of code development

~ 2003 last installations replaced

Martin Grötschel


Slide21 l.jpg

All other companies did basically the same;but it is hard to find out what they really did.

Martin Grötschel


Surprise l.jpg
Surprise

  • Due to expertise and practical experience, the HOT specialists were able to come up with very good (and often almost optimal) solutions when “number of busses” was the major objective.

Martin Grötschel


Single depot vehicle scheduling l.jpg
Single Depot Vehicle Scheduling

1

2

3

4

3

6

7

3

3

7

8

10

1

2

3

  • The Assignment Problem

    • Input: 3 Buses, 3 trips, costs

    • Output: cost minimal assignment

Buses

Solution

Cost = 20

Trips

Martin Grötschel


Single depot vehicle scheduling24 l.jpg
Single Depot Vehicle Scheduling

1

2

3

4

3

6

7

3

3

7

8

10

1

2

3

  • The Greedy-Heuristik

    • heuretikos (gr.): inventiveheuriskein (gr.): to find

Buses

Solution

Cost = 17

Trips

Martin Grötschel


Single depot vehicle scheduling25 l.jpg
Single Depot Vehicle Scheduling

1

2

3

4

3

6

7

3

3

7

8

10

1

2

3

  • The Greedy-Heuristik

    • heuretikos (gr.): inventiveheuriskein (gr.): to find

Busses

Solution

Cost = 16

Trips

Martin Grötschel


Single depot vehicle scheduling26 l.jpg

The "Primal Problem"

Minimum Cost

Assignment

The "Dual Problem"

Maximum Sales Revenues

"Shadow Prices"

Single Depot Vehicle Scheduling

5

4

0

4

3

6

7

3

3

7

8

10

7

8

9

Buses

Optimum

Cost = 15

Trips

Martin Grötschel


Mathematical models assignment problem l.jpg

Graph Theoretic Model

Integer Programming Model

Linear Programming Relaxation

Mathematical Models(Assignment Problem)

2

1

3

4

7

3

6

3

3

10

8

7

3

2

1

Martin Grötschel


Single depot vehicle scheduling28 l.jpg
Single Depot Vehicle Scheduling

0

0

0

4

4

3

3

6

6

7

7

3

3

3

3

7

7

8

8

10

10

0

0

0

  • The „Successive Shortest Path“ Algorithm

Martin Grötschel


Single depot vehicle scheduling29 l.jpg
Single Depot Vehicle Scheduling

0

0

0

0

0

0 0

0

0

0

4

4

3

3

6

6

7

7

3

3

3

3

7

7

8

8

10

10

0

0

0

  • The „Successive Shortest Path“-Algorithm

Buses

Bound

cost = 15

Partial sol.

cost = 0

Trips

Martin Grötschel


Single depot vehicle scheduling30 l.jpg
Single Depot Vehicle Scheduling

0

0

0

0

0

0 0

0

0

0

4

0

3

0

6

2

7

4

3

0

3

0

7

4

8

5

10

6

0

0

0

  • The „Successive Shortest Path“ Algorithm

Buses

+0

+0

+0

Bound

cost = 10

Partial sol.

cost = 3

Trips

+3

+3

+4

Martin Grötschel


Single depot vehicle scheduling31 l.jpg
Single Depot Vehicle Scheduling

  • The „Successive Shortest Path“ Algorithm

0

0

0

0

0

0 0

Buses

0

0

0

Bound

cost = 10

Partial sol.

cost = 3

4

0

3

0

6

2

7

4

3

0

-3

0

7

4

8

5

10

6

Trips

3

3

4

Martin Grötschel


Single depot vehicle scheduling32 l.jpg
Single Depot Vehicle Scheduling

  • The „Successive Shortest Path“ Algorithm

0

0

0

0

0

0 0

Buses

0

+0

+0

0

0

+0

Bound

cost = 10

Partial sol.

cost = 6

4

0

3

0

6

2

7

4

3

0

-3

0

7

4

8

5

10

6

Trips

3

+0

3

+0

4

+0

Martin Grötschel


Single depot vehicle scheduling33 l.jpg
Single Depot Vehicle Scheduling

  • The „Successive Shortest Path“ Algorithm

0

0

0

0

0

0 0

Buses

0

0

0

Bound

cost = 10

Partial sol.

cost = 6

4

0

-3

0

6

2

7

4

-3

0

3

0

7

4

8

5

10

6

Trips

3

3

4

Martin Grötschel


Single depot vehicle scheduling34 l.jpg
Single Depot Vehicle Scheduling

  • The „Successive Shortest Path“ Algorithm

0

0

0

0

0

0 0

Buses

0

+4

+5

0

0

+0

Bound

cost = 15

Partial sol.

cost = 15

4

0

-3

0

6

2

7

4

-3

0

3

0

7

4

8

5

10

6

Trips

3

+4

3

+5

4

+5

Martin Grötschel


Single depot vehicle scheduling35 l.jpg
Single Depot Vehicle Scheduling

  • The „Successive Shortest Path“ Algorithm

0

0

0

0

0

0 0

Buses

5

4

0

Bound

cost = 15

Partial sol.

cost = 15

-4

0

-3

0

6

1

7

0

3

0

3

1

7

3

-8

0

10

1

Trips

7

8

9

Martin Grötschel


Single depot vehicle scheduling36 l.jpg
Single Depot Vehicle Scheduling

5

4

0

4

0

3

0

6

1

7

0

3

0

3

1

7

3

8

0

10

1

7

8

9

  • The „Successive Shortest Path“ Algorithm

    • Path Search

    • Solution + Proof

    • Efficient

Buses

Bound

cost = 15

Solution

cost = 15

Trips

Martin Grötschel


Slide37 l.jpg
SPEC

Andreas Löbel

Martin Grötschel


Contents38 l.jpg
Contents

  • What is vehicle circulation/scheduling?

  • Single depot vehicle scheduling

  • Multiple depot vehicle scheduling

  • Extensions

Martin Grötschel




Vehicle scheduling l.jpg
Vehicle Scheduling

  • InputTimetabled and deadhead tripsVehicle types and depot capacitiesVehicle costs (fixed and variable)

  • OutputVehicle rotations

  • ProblemCompute rotations to cover all timetabled trips

  • GoalsMinimize number of vehiclesMinimize operation costsMinimize line hopping etc.

vehiclecirculationsrotationsblocksschedules

Martin Grötschel


Graph theoretic model l.jpg
Graph Theoretic Model

deadhead trips

pull-out trips

pull-in trips

timetabled trips

Martin Grötschel


Example regensburg l.jpg
Example: Regensburg

Map deleted

Martin Grötschel


Vehicle scheduling44 l.jpg
Vehicle Scheduling

Depot capacities: soft upper limits

Fleet minimum: pull-in trips

No line changes: interlining trips

Peaks: pull-in/pull-out trips

Turning: turns

  • Definition + cost of deadhead trips

    • Precise control at point, time, or trip

    • Changes of vehicles, lines, modes, turning, etc.

    • Automatic generation of pull-in/pull-out trips

    • Maintencance of all possible deadhead trips

  • Depot capacities (soft)

Martin Grötschel


Timelines l.jpg
Timelines

d

d

Needs Fow model

assignment model will be too large

Martin Grötschel


Integer programming model multicommodity flow problem l.jpg
Integer Programming Model(Multicommodity Flow Problem)

Martin Grötschel


Theoretical results l.jpg
Theoretical Results

  • Observation: The LP relaxation of the Multicommodity Flow Problem does in general not produce integeral solutions.

  • Theorem: The Multicommodity Flow Problem is NP-hard.

  • Theorem (Tardos et. al.): There are pseudo-polynomial time approximation algorithms to solve the LP-relaxation of Multicommodity Flow Problems which are faster than general LP methods.

Martin Grötschel


Lagrangean relaxation l.jpg
Lagrangean Relaxation

f3

x2

x1

f2

f4

P(A,b)P(B,d)

f

P(A,b)

f1

x3

x4

Martin Grötschel


Bundle method kiwiel 1990 helmberg 2000 l.jpg
Bundle Method(Kiwiel [1990], Helmberg [2000])

2

1

3

  • Max

    X polyhedral (piecewise linear)

f

Martin Grötschel


Primal approximation l.jpg
Primal Approximation

  • Theorem

converges to a point

Martin Grötschel


Quadratic subproblem l.jpg
Quadratic Subproblem

(1)

(2)

(3)

Martin Grötschel


Bundle method ivu41 838 500 x 3 570 10 5 nnes per column l.jpg
Bundle Method(IVU41 838,500 x 3,570, 10.5 NNEs per column)

450

400

350

300

250

200

bundle

volume

barrier

cascent

150

100

50

20

40

60

80

100

120

140

sec

Martin Grötschel


Lagrangean relaxation i l.jpg
Lagrangean Relaxation I

Martin Grötschel


Lagrangean relaxation i54 l.jpg
Lagrangean Relaxation I

  • Subproblem: Min-Cost-Flow (single-depot)

Martin Grötschel


Lagrangean relaxation ii l.jpg
Lagrangean Relaxation II

Martin Grötschel


Lagrangean relaxation ii56 l.jpg
Lagrangean Relaxation II

  • Subproblem: Several independent Min-Cost-Flows (single-depot)

Martin Grötschel


Heuristics l.jpg
Heuristics

  • Cluster First – Schedule Second

    • "Nearest-depot" heuristic

    • Lagrange Relaxation II + tie breaker

  • Schedule First – Cluster Second

    • Lagrange relaxation I

  • Schedule – Cluster – Reschedule

    • Schedule: Lagrange relaxation I

    • Cluster: Look at paths

    • Solve a final min-cost flow

  • Plus tabu search

Martin Grötschel



Computational results l.jpg
Computational Results

Martin Grötschel


Vehicle utilization l.jpg
Vehicle Utilization

Martin Grötschel


Camel curve l.jpg
"Camel Curve"

68

Martin Grötschel


Interlining l.jpg
Interlining

too short to turn

too long to wait

best choice

Martin Grötschel


Umlaufoptimierung l.jpg
Umlaufoptimierung

Umlaufoptimierung mit MICROBUS 2

Erzielte Einsparungen durch die Umlaufoptimierung:

Im Busbereich wurden bei einer Gesamtzahl von knapp über 200 Fahrzeugen 5 Busse eingespart.

Im Bahnbereich wurden aufgrund der fehlenden Leerfahrt- und Überholmöglichkeiten keine Fahrzeuge eingespart.

Slide of SWB

Martin Grötschel

Heiko Klotzbücher

4

26.02.2002


Vehicle scheduling at zib l.jpg
Vehicle Scheduling at ZIB

Martin Grötschel


Vehicle scheduling at zib65 l.jpg
Vehicle Scheduling at ZIB

  • Ralf Borndörfer

  • Andreas Löbel

    Ramifications:

  • Corinna Bönisch

  • Ines Spenke

  • Steffen Weider

Martin Grötschel


Bvg berlin l.jpg
BVG (Berlin)

Martin Grötschel


Contents67 l.jpg
Contents

  • What is vehicle circulation/scheduling?

  • Single depot vehicle scheduling

  • Multiple depot vehicle scheduling

  • Extensions

Martin Grötschel


Discussion extensions l.jpg
Discussion/Extensions

  • Properties

    • Exploiting all degrees of freedom

    • Vehicle mix

  • Extensions

    • Trip shifting  current work

    • Multiperiod scheduling

    • Periodic schedules

    • Assimilation

    • Balanced depot exchange

    • Maintenance constraints

    • Integration

      • Vehicle and duty scheduling  current work

      • Timetabling

      • Line planning

Martin Grötschel


Trip shifting l.jpg
Trip Shifting

Martin Grötschel


Vehicle circulation and the hungarian method70 l.jpg

Vehicle Circulation andthe Hungarian Method

The END

Thank you for your attention

Martin Grötschel

joint work with

Ralf Borndörfer Andreas Löbel Steffen Weider

A celebration day of the 50th anniversary of the Hungarian MethodBudapest, October 31, 2005