Problem formulation guidance
Decision problems from other platforms are formulated with clear objectives, constraints and uncertain parameters before a method is chosen.
GCRI · Systems Science and Modelling
Optimisation methods
Optimisation and operations research is a method this platform stewards. It provides formulations and solvers for allocating resources, designing systems and scheduling actions, with methods for uncertainty that other platforms apply to their own problems.
01Contents
Optimisation methods in five parts.
02Application
What optimisation and operations research does here.
Optimisation and operations research develop mathematical methods for allocating resources and making decisions under constraints. They support planning and logistics in complex, interconnected systems. In methods and modelling, risk management and systemic risk and research and evidence, optimisation supports prepositioning of supplies, network investment and recovery sequencing. Robust formulations help choose options that perform acceptably across many scenarios. The canonical description is on the STEM Commons.
Robust and stochastic comparisons
Deterministic, stochastic and robust formulations are solved for the same problem to show what each gains and costs.
Solver benchmarking
Open-source and commercial solvers are benchmarked on representative problems so platforms can choose tools that fit.
03Monitor
Optimisation run.
The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.
Optimisation run
Systems science · Optimisation methods · Run R-1320
Feasible, gap closingGCRI · Systems Science and Modelling
Convergence
Method card
- Method
- Optimisation and operations research
- Variables
- 34,656
- Optimality gap
- 1.3 pct
- Label
- MODELLED
Binding constraints
| Capacity | 0 | 5 | Binding |
| Budget | 0 | 1.4 | Binding |
| Service level | 7 | 0 | Slack |
04Data
What the method consumes.
Datasets and records used by optimisation and operations research on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Benchmark problem libraries | Testing | REPORTED |
| Platform decision problems | Applications | DECLARED |
| Scenario sets | Uncertainty | MODELLED |
05Methods and evidence
How optimisation methods is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Model, equations and assumptions
The model structure used for optimisation methods, the assumptions it makes and how each is tested.
Risk of element i
Ri = f(Hi, Ei, Vi, Ci)hazard, exposure, vulnerability and coping capacityExpected annual loss
EAL = ∑k pk · Lkover events k with annual probability pkCoupled systems
xt+1 = A xt + B ut + εtA carries the couplings, u the shock, ε the error| Assumption | Why it is made | How it is tested |
|---|---|---|
| Hazard and exposure are independent within an event | Keeps the loss integral tractable | Compare with a copula fit on joint records |
| Couplings are linear near the operating point | Lets shocks propagate through A | Perturb beyond the linear range and compare |
| Vulnerability curves transfer between places | Local curves are rarely available | Validate against observed losses where they exist |
- Inputs
- versioned datasets with provenance
- Outputs
- distributions, never single numbers
- Code
- released with the model card and tests
- Reproduction
- same data, code, environment and seed
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
06Validation
How results are checked.
Solutions are checked for feasibility, tested through simulation and compared with historical decisions. Sensitivity analysis examines how results change with parameters.
| Check | How it is done |
|---|---|
| Formulation review | Formulations are reviewed with domain experts |
| Solution verification | Solutions are checked for feasibility and optimality gaps |
| Out-of-sample testing | Plans are tested on scenarios not used to choose them |
Optimal solutions can be fragile when assumptions are wrong. Objectives may omit values that are hard to quantify.
07Process
How the process runs.
Process
Optimisation methods: N-1 contingency assessment
The EU System Operation Guideline names contingency lists, analysis and handling; Nexus describes no N-1 process, so only these steps are shown.
01 Inputs
- 01Network state and modelRecord · The system operatorThe analysis starts from the operating state and network model of the system operator. Their content is set by that operator.
02 Assessment
- 02Contingency listRecord · The system operatorThe System Operation Guideline lists contingency lists as a named step. The list contents are set by the operator and are not stated here.
- 03Contingency analysisModel · The system operatorThe System Operation Guideline lists contingency analysis as a named step. The method, tools and limits are not stated here.
- 04Contingency handlingStep · The system operatorThe System Operation Guideline lists contingency handling as a named step. What it requires is not stated here.
03 Operator
- 05Operators decide; the programme controls no gridActor · The operatorWater and power operators decide any real-world change to their systems. Exercises give the programme no control of operational technology.
A national mission · Decision rightsOutline of an externally published process, not a Nexus process and not a record of operation. The published Nexus documents describe no N-1 assessment. No programme runs one and every programme is at service level R0.
08Connections
Topics that rely on this method.
09Stewardship
Who maintains the method.
Systems Science and Modelling stewards optimisation and operations research for the Consortium and reviews how it is applied across platforms.
10Questions
Questions and answers.
What are the limits of optimisation and operations research in this field?
Optimal solutions can be fragile when assumptions are wrong. Objectives may omit values that are hard to quantify.
How are results checked?
Solutions are checked for feasibility, tested through simulation and compared with historical decisions. Sensitivity analysis examines how results change with parameters.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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