Programme Studio · Project Co-design

Director brief

Compare the minimal alternatives

Not solved

Feasible candidates

All plans surviving the hard ceilings.

Pareto-minimal plans

The antichain under <capex, months, risk, access days>.

Highlighted plan

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Selected using the current recommendation lens.

Least relative headroom

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Computed from the selected habitat plan.

Set the task and press Recompute frontier. The model will choose crossing width, connected catchment, compatible packages, governance, and stage strategy, then filter for minimal resource bundles.

Start here: a request, a compatible design, and its trade-offs

Functionality is the promise.

Here it is model crossings/day: width × connected catchment × a declared scenario coefficient. This fictional capability is not measured animal passage. A design is a particular habitat plan and package tuple. Resources are what that implementation requires: capex, duration, programme risk and access days. Green dashed diagram edges show provided capabilities; red solid edges show resource requirements. Each component provides an envelope and also requires a resource bundle; the selected implementation keeps both sides together.

One choice can require a co-move.

In this fictional catalogue, a wider crossing requires more connected guide fencing and survey coverage. A 30 m plan drawing on 2 km of catchment still requires 3 km of fencing, and nine monitoring stations in the mixed landscape. These are declared package rules, not universal engineering or ecological laws.

Monotone does not mean irreversible.

Holding the catalogues and assumptions fixed, asking for more model crossing capability can only remove feasible implementations. It does not force the user to keep the highest target ever tried. A signed commitment or an irreversible construction step is an additional project rule and needs its own model. You can freely explore a lower request here.

Several minimal choices can be useful.

A cheaper plan may take longer or use more access days. Here access-day equivalents aggregate disruptive work windows after declared multipliers; they are not a dated road-closure plan. Pareto dominance means no worse in every resource and strictly better in at least one. The remaining alternatives form a discussion object: compare the extra resource needed for a gain, without forcing everyone’s objectives into one score. Balanced is only an illustrative initial highlight; a hypothetical risk ceiling is not stakeholder consent.

The other essays share this wildlife-crossing scenario, but their catalogues and numerical scales are separate teaching models. For generated legal work sequences and construction-period readiness constraints, open the staged-path experiment.

Executive reading

Select a retained implementation to inspect its functionality, compatible subsystem tuple and resource consequences.

Task decomposition

Provide model crossing capability
meet the declared capacity request

Provide a suitable crossing width
vegetated structure envelope

Connect the required approaches
guide fencing, ramps and access gates

Observe the installed envelope
camera stations and survey commissioning

Keep the programme governable
claims, approvals, stakeholder tolerance

Programme algebra

Capex
Package costs are summed, then context, governance and declared premiums apply.

Schedule
Parallel work uses a max-like critical-path logic, then adds interface / approval delay.

Risk
Mismatch, access days, and governance discipline are merged, then optionally fed back into schedule.

The selected implementation: actual component joins

The same three provided ≥ required checks select this tuple in the engine and appear in the dependency diagram. Package quantities are available envelopes: the plan commissions its required extent and monitoring covers that extent, not unused spare capability. Guide fencing may exceed connected catchment to include returns and escape approaches. These endpoint checks do not certify animal passage during works.

Select a plan to inspect its component joins.

What the highlighted plan is really saying

Once solved, this panel explains the highlighted plan in programme language: what it buys, what it forces elsewhere, and which declared assumptions drive its programme penalties.

Data flow vs logical dependency

The dependency view displays the selected tuple’s actual provided ≥ required checks. The movement view is a separate conceptual sketch.

On a narrow screen, scroll the diagram sideways to read its labels.

Stage alignment diagnosis

Select a plan to inspect normalized subsystem readiness in its base construction pattern. The separate clock breakdown accounts for programme-level delay; neither display certifies animal passage during works.

Method in six moves. Define the task, identify the implementing components, join their provided and required capabilities, retain compatible alternatives, evaluate their resources, and query the minimal tuples. The feedback panel is a separate affine resource calculation; it is not a general solver for cyclic co-design diagrams.

What to ask the component teams

Before modelling a real programme, ask each team for alternatives: what each can provide, what it requires from other components, and the resources it consumes, with units, evidence and a stated validity range. For the crossing, ask the structure team for width and land/cost options, the landscape team for guiding-fence obligations, and the monitoring team for observation and staffing options. Agree which provided capability satisfies each requirement before comparing complete designs.

Keep permissions and stakeholder decisions explicit. A compatible model supplies evidence for discussion; it does not grant approval. This practical habit is retained from the earlier director’s guide; its unchecked calculator is superseded by the four current essais.

1 · Define the task

The task is: deliver corridor model crossing capability under explicit ceilings on budget, time, and programme risk. The page treats this as the top-level function and keeps implementation choices separate from it.

2 · Functional decomposition

The external function is model crossing capability. A habitat plan specifies width and connected catchment; the three package catalogues provide the capabilities required by that plan. A works implementation also includes a governance choice and a supplied staging pattern. The no-project implementation uses compatible baseline assets.

3 · From decomposition to co-design diagram

The actual joins are explicit: crossing width ≥ planned width; guide-fence length ≥ max(planned catchment, the width-induced minimum); camera stations ≥ the rounded-up survey coverage requirement. The selected tuple’s checks are shown in the Brief. Diagram arrows illustrate these dependencies; they do not simulate animal behaviour.

4 · Populate implementations

The implementation set is the compatible subset of the Cartesian product of the finite catalogues, with the habitat plan and programme alternatives retained. Flat enumeration computes these joins directly. The catalogue relation is discrete; readiness sampling and risk assumptions remain approximations of the chosen scenario.

5 · Solve by querying minimal resources

For the requested model crossing capability, the solver retains all compatible implementations that meet the declared ceilings, then finds the minimal resource tuples across them. Raising only the model crossing capability request removes implementations; it never changes a fixed implementation’s cost or risk.

6 · Treat loops explicitly

For a fixed implementation, the supplied affine map is r = B + 0.72q + 0.222P + 0.42αr. Every supplied α gives slope below one, so the exact solution is r = (B + 0.72q + 0.222P)/(1 − 0.42α). The trace illustrates iteration; the resource evaluation uses this exact result.

Stylised modelling choices in this scenario

Packages, durations, governance effects and penalties are illustrative. Capacity requirement maps are non-decreasing; resource bundles are Pareto-filtered. Sequencing is restricted to four supplied strategies. Readiness is linearly interpolated within work stages and mismatch is sampled at 120 intervals; it is not certified animal passage during works. The feedback calculation is a synthetic scalar evaluator, not a general MCDP loop solver. Resource ceilings of zero are unconstrained; there are no hidden duration or risk cutoffs. The no-project option has zero incremental resources only when the baseline packages are compatible and meet the task.

Pareto frontier

x = capex, y = schedule, bubble = risk, outline = Pareto-minimal. Click a row below to inspect a plan.

feasible plan minimal plan

Dominance reading

The green-outlined points form an antichain: no distinct retained resource tuple dominates another across all four dimensions. Dominance also compares access days, which this two-axis projection does not fully display. The table retains all four resource coordinates.

Feasibility split

The bar chart decomposes feasible candidates by stage strategy and governance mode, showing where the antichain comes from institutionally.

Minimal plans table

The recommendation lens only highlights a row. The antichain itself remains the correct decision object.

0 plans

Why this loop exists. This model assumes that mismatched subsystem delivery increases an illustrative approvals burden, which lengthens the programme and feeds back into its risk index. Those relationships are declared scenario assumptions, not identified causal effects or empirical claims about ecological outcomes.

Iteration trace

The trace shows risk ↗ approvals delay ↗ schedule ↗ risk from zero. The final row is the exact affine solution used by the resource query, not a tolerance-limited estimate.

Loop read-out

Solve the frontier and select a plan to see its fixed-point trace.

A finite counterexample to an automatic cutoff. With T₀ = 400 months, B = 600 risk units, q = 200 months, A = 100 access-day equivalents and α = 0.085, the equations give T = 677.54 months and r = 794.57. These intentionally extreme test inputs are not a catalogue programme or recommendation. They show why finite values must not be silently rejected by an undisclosed 180-month or 260-risk cutoff. Declared user ceilings still apply.

This is one declared scalar resource evaluator. A general MCDP feedback operator over design relations is a different construction and is not implemented here. With feedback off, the model uses the stated nonrecursive base, mismatch and access-day terms.

Explanatory model notation

This sketch is not executed or validated MCDPL syntax. The actual finite JavaScript relation checks the component joins shown in the Brief and enumerates their compatible tuples. Inspect the model note for the implemented equations.

Glossary

Functionality = what a subsystem provides.
Resources = what it requires.
Catalogue = arbitrary discrete implementation relation.
Choose = retain one explicit programme alternative.
Antichain = mutually non-dominating minimal plans.
Scalar feedback here = an affine schedule/risk evaluator with an exact fixed point.

Interpretive note

The point of the exercise is not to make wildlife crossing projects look like a single spreadsheet optimisation. It is to formalise the fact that every local improvement pushes on a wider dependency structure, and that management choices about packaging and pacing are themselves part of the design space.