Helsinki University of Technology Systems Analysis Laboratory INFORMS Seattle 2007 Integrated Multi-Criteria Integrated Multi-Criteria Budgeting for Maintenance and Budgeting for Maintenance and Rehabilitation Policies at the Rehabilitation Policies at the Finnish Road Administration Finnish Road Administration Pekka Mild and Ahti Salo Systems Analysis Laboratory Helsinki University of Technology (TKK) P.O. Box 1100, 02015 TKK, Finland
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Pekka Mild and Ahti Salo Systems Analysis Laboratory Helsinki University of Technology (TKK)
Integrated Multi-Criteria Budgeting for Maintenance and Rehabilitation Policies at the Finnish Road Administration. Pekka Mild and Ahti Salo Systems Analysis Laboratory Helsinki University of Technology (TKK) P.O. Box 1100, 02015 TKK, Finland. Finnish Road Administration (Finnra) - PowerPoint PPT Presentation
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Helsinki University of Technology Systems Analysis Laboratory
INFORMS Seattle 2007
Integrated Multi-Criteria Budgeting for Integrated Multi-Criteria Budgeting for Maintenance and Rehabilitation Policies Maintenance and Rehabilitation Policies
at the Finnish Road Administrationat the Finnish Road Administration
Pekka Mild and Ahti SaloSystems Analysis Laboratory
Helsinki University of Technology (TKK)
P.O. Box 1100, 02015 TKK, Finland
Helsinki University of Technology Systems Analysis Laboratory
2INFORMS Seattle 2007, Pekka Mild and Ahti Salo
Road asset management in FinlandRoad asset management in Finland
Finnish Road Administration (Finnra)– Central administration and 9 road districts
– Maintenance, repair and investments mgmt
– Research and development
Road network– 78000 km of public roads
– 14000 bridges
Estimated asset value 21 billion USD– Around 4000 USD per capita
– Annual funding around 850 million USDPave-ments
Brid-ges
Gravel Roads
Road Equip-ment
OtherRoad Assets
ROAD ASSET MANAGEMENT
DATA
UTILISATION
Data collection and manage-ment
I
II
III
IV
Road Asset Management methodology
Utilisation of road manage-ment data
Total Highway Manage-ment
METHODS
INFRASTRUCTURE ASSETS
Pave-ments
Brid-ges
Gravel Roads
Road Equip-ment
OtherRoad Assets
ROAD ASSET MANAGEMENT
DATA
UTILISATION
Data collection and manage-ment
I
II
III
IV
Road Asset Management methodology
Utilisation of road manage-ment data
Total Highway Manage-ment
METHODS
INFRASTRUCTURE ASSETS
Road asset management researchprogram 2003-2007
Helsinki University of Technology Systems Analysis Laboratory
3INFORMS Seattle 2007, Pekka Mild and Ahti Salo
Programmed rehabilitation and reconstruction projects
Maximize the long-term sum of all products’ multicriteria value– Time horizon of 30 years with 3% p.a. discount rate
– Budget constraints and quality targets
– Decision variables: repair actions and levels of maintenance operations» Number of quality class 1 bridges repaired to class 4 in year 2008
» Kilometers held at winter maintenance quality class 3 in year 2012
– Repair and deterioration dynamics captured by linear constraints
Different weights suggest different optimal allocations – Sample the feasible weight set determined by the rank-ordering
Helsinki University of Technology Systems Analysis Laboratory
9INFORMS Seattle 2007, Pekka Mild and Ahti Salo
Key results for managementKey results for management
Which resource allocation policies maximize the long-term multicriteria value of the whole road system?– Which products call for more funding when customer satisfaction
becomes a key priority?
– What do criteria weightings imply for the products’ funding needs?
– What is the expected interim/terminal quality distribution of the system?
What is the ”pecking order” of the products?– Which products gain/lose funding when the overall budget is changed?
– Which products gain/lose funding first and which later?
– What do different weightings imply for the ”pecking order”?
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cate
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MIN: Bridges
AVE: Bridges
MAX: Bridges
AVE: Pavements
MIN: Pavements
MAX: Pavements
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Year
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cate
d to
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cat
egor
y [M
€]
Road equipment (prog.)
Winter-time (maint.)
Bridges (prog.)
Road surroundings (maint.)
Gravel roads (maint.)
Gravel roads (prog.)
Pavements (prog.)
Computed
Helsinki University of Technology Systems Analysis Laboratory
10INFORMS Seattle 2007, Pekka Mild and Ahti Salo
Integrated platformIntegrated platformfor collaborative for collaborative management of management of the entire systemthe entire system
$
……
Helsinki University of Technology Systems Analysis Laboratory
11INFORMS Seattle 2007, Pekka Mild and Ahti Salo
Client feedbackClient feedback
Best project award in Finnra’s road asset management research program
”An innovative tool for thinking and communication” – Antti Rinta-Porkkunen, Director of the South-East Finland road district
”Framework to bring the managers of separated products to facilitated interaction and give them fresh insights about the aggregate system” – Vesa Männistö, Senior Consultant, Pöyry Infra Ltd.
Enthusiasm for optimization and decision analysis at Finnra
Helsinki University of Technology Systems Analysis Laboratory
12INFORMS Seattle 2007, Pekka Mild and Ahti Salo
Novel methodological elements in our caseNovel methodological elements in our case
From technical condition-focus to value-focus– Explicit value models for quality classes
From product orientation to portfolio optimization – Incomplete preference information through rank-orderings
From static budgeting to long-term allocations – Integrated repair and deterioration dynamics of products
From turf-fights to collaborative learning – Interactive work-shop with ’on-the-fly’ computations
Helsinki University of Technology Systems Analysis Laboratory
13INFORMS Seattle 2007, Pekka Mild and Ahti Salo
Towards integrated sustainable planning Towards integrated sustainable planning
– Has far-reaching impacts on societies, industries and individuals
– Involves multiple objectives, long planning horizons, high uncertainties
There is major untapped potential for Decision Analysis– Value-focused analysis of individual products and product portfolios
– Explicit recognition of stakeholders’ interests and preferences
– Use of DA models as vehicles for enhanced communication
– A paradigm shift towards integrated collaborative planning
Helsinki University of Technology Systems Analysis Laboratory
14INFORMS Seattle 2007, Pekka Mild and Ahti Salo
Thank you!Thank you!
Questions?Questions?
Helsinki University of Technology Systems Analysis Laboratory
15INFORMS Seattle 2007, Pekka Mild and Ahti Salo
Appendix: LP-model formulation (1/3), variables & dynamicsAppendix: LP-model formulation (1/3), variables & dynamics Decision variables (product i, class j, year t)
– Quantity distribution:
– Amount (kilometers, units) moved from j to j’: ,0)(' txi jj
Linear repair and deterioration dynamics– Percentage of quantity deteriorates, i.e., drops to in one year– for all maintenance operations products– Linear constraints
– Slightly different constraints for boundary states (1 and 5)– Set of allowed state transitions can be restricted product-wise
,0)( tq ij j
ij
j
ij tqtq )()( 0
)()('
' tqtx ij
j
ijj
ijd )(tq ij )(1 tq ij
0ijd
jj
ijj
jj
ijj
ij
ij
ij
ij
ij txtxtqdtqdtq
''
''11 )()()()()1()1(
Remains in class j Deteriorates from class j+1
Moved upwardsfrom j to j’
Moves that arrive at j from below j’
Helsinki University of Technology Systems Analysis Laboratory