Multi Criteria Cross Asset Optimization and Trade-Off Analysis for Asset Management Planning and Programming
Dr Wei LiuPrincipal Asset Management Engineer
GHD
Global Infrastructure Stock and Gap
To bridge the gap, more effective planning of capital and maintenance investment plays a key part in a holistic solution
“Come 2045, an expected 1.2 million more people will live in New Zealand, leading to an amplified demand for efficient infrastructure services.
Now more than ever, the New Zealand government must work with various stakeholders to ensure sound infrastructure planning, which is vital to both the economic growth and well-being of cities.
Planning occurs in silos won't deliver the right results…“
Hon Bill English
Challenges in Asset Management Capital and Maintenance Planning
• Diverse projects and requirements
• Highly constrained budgets• Align project portfolio with
agency’ goals (e.g. KPIs)• Tools and processes to
consistently and objectively prioritise and optimise project planning are not in place.
How We Address the Challenges?
Project Pool
Transport
Water Building
Other Assets …
Multi-Criteria Analysis
Cross- Asset Optimisation & Trade-off
Cpex/Opex LTP
Analysis Inputs– Number of Years for Planning– Project pool
• Business Area, Category and sub-category• Costs (can be staged in multi years)• Impacts (e.g. KPI contributions)
– Multi-Criteria Analysis• Business KPIs and their relative importance• Rules for project scoring and ranking
– Cross Asset Optimisation And Trade-off Analysis• Objective Function• Constraints (budgets and/or performances)
Outcomes from Analysis– Project (overall or by business unit)
ranking list (most to least valuable) – Optimal project mix to deliver on agreed
KPI’s– Optimised multi-year forward work
programme– Optimal fund allocations among business
unit and asset category– Programme cost (total, and per annum),
by business unit– KPI delivery tracking/forecasting
Example: Multi-Criteria Project AssessmentEvaluate and rank projects across investment areas with rationale and consistency
Ranking of Project by Overall Scores
Example: LoS per $ invested analysisunderstand payback for each $ invested
0 20 40 60 80 100 1200
20
40
60
80
100
120
Cost ($M)
Net
wor
k Pe
rfor
man
ce
(NAA
SRA)
0 10 20 30 40 50 60 70 80 90 1000
0.51
1.52
2.53
3.54
Cost ($M)
Brid
ge C
ondi
tion
0 5 10 15 20 25 30 35 40 450
2
4
6
8
10
12
Cost ($M)
FS C
rash
Rat
e
0 100 200 300 400 500 6000
102030405060708090
Cost ($M)
Aver
age
Spee
d
Example: Optimised road maintenance programme (ONRC - levels of service delivery)
Optimised
Optimised
Example: Testing Different Optimisation Strategies
Maximise BCRBudget constraint
Maximise BCRBudget + performance
constraints Min Difference Performance and
Targets
Max Budget Utilisation
Minimise Cost
Example: Trade-off Analysis for two Projects/Portfolios
Summary• Multi-Criteria Cross Asset Optimisation and Trade-off Analysis
Framework and Tool: – Consistent and objective project scoring, ranking and prioritisation process– Flexible optimisation configurations
– Ability to set up and run different objective function – Ability to accommodate various number and type of constraints,
including budget constraints and performance constraints in one year or multiple years.
– Suitable for all level of analysis, from strategic budget analysis to operational project analysis
– Capable to run cross-sector, cross-asset, or cross-class fund allocation analysis
Summary• Future development Plan:
– Risked Based Analysis (e.g. considering budget uncertainties)
– Multi Objective Optimisation– Web App Development
Optimisation Module in dTIMS
Optimisation Engine for Our Tool
Top Related