Integrated Multi-Criteria Budgeting for Maintenance and Rehabilitation Policies at the Finnish Road Administration

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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

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Road 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 USD

Road asset management researchprogram 2003-2007
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How to allocate funds among road keeping products?

• All products impact the same road system
• No integrated management system to-date ? static
  funding patterns
• Yet, sustainable development calls for dynamic
  (re)allocations

?
?
?
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Road products and evaluation criteria
Road districts annual rehabilitation and
maintenance budget
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Value-focused evaluation of products

• TKK-facilitated one-day workshop
• 10 experts from Finnra and Pöyry Infra Ltd.
• Score elicitation
• Intermediate scores by adjusting the shape of the
  value functions for each product
• Maximum scores by comparing inter-product swings
  from the worst quality class to the best
• These two phases repeated for all four criteria
• Weight elicitation
• Incomplete rank information about maximum swings
  under each criterion

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Aggregate multicriteria value of products
bridges quality class distribution
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Deterioration and repair dynamics of products

• Products deteriorate towards worse quality
  classes over time
• Repairs raise quality

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Optimal resource allocations

• 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

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Key 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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Integrated platformfor collaborative management
of the entire system
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Client feedback

• Best project award in Finnras 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

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Novel 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

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Towards integrated sustainable planning

• Infrastructure transportation asset management
• Consumes enormous financial resources globally
• 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

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Thank you!Questions?
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Appendix 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

• 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

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Appendix LP-model formulation (2/3), objective
function

• Evaluation score (product i, class j, criterion
  k)
• Value of distribution (product i, criterion k,
  year t)
• qij(t) quantity of product i in class j in year
  t
• Overall value of distribution (product i, year t)
• wk weight of criterion k (incomplete weighting
  w?Sw)
• Overall value of all products (year t)
• Sum of all products distributions overall
  values
• Total overall value discounted over 30 years
• Objective function in the optimization

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Appendix LP-model formulation (3/3), costs
constraints

• Costs
• Programmed repairs (i ? REP) unit cost per move
  is
• Maintenance operations (i ? MNT) unit cost of
  service level is
• for i ? MNT (shifts are free but
  the resulting quantity comes to cost)

• Budget constraints
• Budget constraints can be set also for any
  subsets of products or moves

• Examples of other constraints
• Gradual change
• (Dynamic) target thresholds for distributions
• E.g., share of poor-conditioned (class 1) bridges
  must be below 1 in year 2015