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