yogsoth-ai Value Maximization
Purpose
Select the portfolio subset that maximizes aggregate value (ROI, impact, utility) subject to resource constraints. Applies when the primary goal is getting the most out of a limited budget.
When to use
- Fixed budget with many candidate investments
- Clear value metrics exist for each candidate
- Constraints are well-defined (cost, time, capacity)
- Goal is maximum total return, not diversity or risk management
Budget
| Dimension | Target |
|---|---|
| Candidates evaluated | 8-20 |
| Constraints modeled | 1-5 |
| Value metrics | 1-3 per candidate |
| Solutions compared | >=5 |
State Ledger
| Field | Type | Description |
|---|---|---|
| candidates | list | All candidate items with value and cost attributes |
| constraints | list | Budget, capacity, or other binding constraints |
| objective_function | string | How value is aggregated (sum, weighted sum, etc.) |
| optimal_solution | list | Selected portfolio maximizing value |
| value_achieved | number | Total value of selected portfolio |
Available Tactics
| Tactic | When |
|---|---|
| pareto-frontier-construction | Multiple value dimensions to trade off |
Available SOPs
| SOP | Purpose |
|---|---|
| objective-definition | Define what "value" means and what constraints bind |
| optimization-run | Run the optimization to find best portfolios |
| pareto-visualization | Visualize value trade-offs if multi-objective |
| selection-from-frontier | Pick final portfolio from candidates |
Execution Guidance
- Define value metric(s) and constraints via objective-definition
- If single objective: solve as knapsack/LP directly
- If multiple objectives: use pareto-frontier-construction tactic
- Select from frontier based on stakeholder preferences
- Validate selected portfolio against all constraints
Output Format
strategy: value-maximization
selected_portfolio:
- candidate: <name>
value: <score>
cost: <cost>
total_value: <aggregate>
total_cost: <aggregate>
constraint_slack: <remaining budget>
method_used: <knapsack|LP|NPV>
confidence: <high|medium|low>
Available Tactics
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use |
|---|---|
| pareto-frontier-construction | Build the Pareto frontier from multi-objective optimization, visualize trade-offs, and select a portfolio from non-dominated solutions. |
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| objective-definition | Define optimization objectives, constraints, and trade-off preferences from context and candidate information. |
| optimization-run | Execute multi-objective optimization on candidates to produce a Pareto front of non-dominated solutions. |
| pareto-visualization | Create visual representation of the Pareto frontier showing trade-offs between objectives with narrative explanation. |
| selection-from-frontier | Select the final portfolio from the Pareto front by applying stakeholder preferences and decision criteria. |