Operations Research¶
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24 primes originate from Operations Research and 39 more draw from it as a secondary origin — sort the Origin column to separate them. They span 15 subdomains; sort by that column to group them, or click any subdomain to filter to it.
| Prime | Origin | Subdomain | Description |
|---|---|---|---|
| Allocation | Primary | — | Assign a limited supply across competing claimants under a feasibility constraint, independent of which criterion fills in the rule. |
| Auction Theory | Also draws from | — | Auction behavior analysis. |
| Batch Processing | Primary | Collect many discrete work-items so a costly setup is paid once and amortised over the group, trading lower per-item cost for higher per-item latency. | |
| Batch Size | Primary | The granularity at which a stream of work is grouped, trading setup cost amortised per item against flow, delay, risk, and feedback-lag costs that rise with the group — producing an interior optimum. | |
| Black Box vs. White Box Distinction | Also draws from | — | Visibility of internal structure. |
| Branch and Bound | Primary | — | Systematic search with pruning. |
| Caching | Also draws from | — | Store for faster retrieval. |
| Comparative Advantage | Also draws from | — | Efficient specialization. |
| Complexity (Time/Space) | Also draws from | — | Resource scaling with input size. |
| Concurrency | Also draws from | — | Manage simultaneous processes. |
| Concurrent, Cross-Functional Collaboration | Also draws from | — | Parallel teamwork. |
| Constraint | Also draws from | — | Limits possibilities to guide outcomes. |
| Cost–Benefit Analysis | Also draws from | — | Evaluate decisions. |
| Cross-Impact Analysis | Also draws from | — | Interacting trends. |
| Deadlock | Also draws from | — | Mutual blocking processes. |
| Decision | Also draws from | — | Committing to one alternative from a set under uncertainty and trade-off, collapsing open deliberation into a chosen path and foreclosing the others. |
| Discounting (Present Value) | Also draws from | — | Present value calculation. |
| Dunning-Kruger Effect | Also draws from | — | The miscalibration in which the skills needed to judge one's own competence are the same skills one lacks, so the least competent most overestimate their ability. |
| Dynamic Programming | Primary | — | Solve via subproblem reuse. |
| Economies of Scale | Also draws from | — | Cost reduction with scale. |
| Efficiency | Also draws from | Judge an input–output arrangement against its feasible alternatives: it is efficient when no alternative preserves or improves the specified result while using fewer resources, and its inefficiency is the dominated slack removable without sacrifice. | |
| Engineering Tolerances | Also draws from | — | Acceptable variation. |
| Extreme Capture Probability | Also draws from | When valuable targets are rare in a large heterogeneous population, a bounded untargeted sample captures them according to its coverage fraction — only n/N for the single best — so expanding reach or targeting matters more than prestige within the same bounded pool. | |
| Gains from Trade | Also draws from | — | Mutual benefit exchange. |
| Incentive Compatibility | Also draws from | — | Align incentives. |
| Incident Response | Primary | A system facing acute, time-critical disruption engages a temporary command regime that prioritises stabilisation over diagnosis, accepts reversible degradation, defers root-cause analysis, and compresses decision authority for the duration of the acute phase only. | |
| Integer Linear Programming (ILP) | Primary | — | Discrete optimization with integer variables. |
| Linear Programming (LP) | Primary | — | Optimize linear objective with constraints. |
| Marginal Analysis | Also draws from | — | Incremental effects. |
| Markov Decision Processes (MDPs) | Primary | — | Sequential decision-making under uncertainty. |
| Mechanism Design | Also draws from | — | Rule engineering. |
| Monte Carlo Simulation | Also draws from | — | Random sampling approximation. |
| Multiobjective Optimization | Primary | — | Balance competing objectives. |
| Network Flow Models | Primary | — | Optimize flow across networks. |
| Network Traversal | Also draws from | Starting from one or more seeds, repeatedly follow eligible edges to visit or expose nodes, so reach and discovery order are determined by topology, frontier policy, and stopping rule. | |
| Optimization | Also draws from | — | Finds best solution under constraints. |
| Parallel Independent Inspection | Primary | Defect coverage of a fixed artifact rises with the number and diversity of independent inspectors working in overlapping parallel. | |
| Pareto Efficiency | Also draws from | — | Optimal allocation. |
| Pipeline | Also draws from | — | Sequential processing stages. |
| Price Discrimination | Also draws from | — | Variable pricing. |
| Price Mechanism | Also draws from | — | Supply-demand pricing. |
| Prioritization | Primary | — | Ordering competing claims on finite resources by a value or urgency metric to produce a ranked sequence of action under constraint, making explicit what gets done first and what does not get done at all. |
| Pull Flow | Primary | An activity is triggered by a downstream demand signal rather than scheduled by an upstream producer, shifting uncertainty absorption from inventory to latency. | |
| Queueing | Primary | — | Organizes tasks into a waiting line based on arrival and service rates. |
| Receptor Saturation | Also draws from | — | Plateau effects at capacity. |
| Resource Management | Primary | — | Allocation of finite assets. |
| Risk Pooling | Also draws from | — | Aggregating many independent or weakly correlated exposures so that the variance of the pooled outcome shrinks below the sum of individual variances, letting participants share a more predictable collective risk. |
| Risk–Return Tradeoff | Also draws from | — | Risk vs reward. |
| Satisficing | Also draws from | — | Accept good-enough solution. |
| Scheduling | Primary | — | Organizing tasks over time. |
| Screening | Also draws from | — | Inducing self-revelation. |
| Sensitivity Analysis (in Operations Research) | Primary | — | Analyze impact of parameter variation. |
| Sequencing | Primary | — | Deliberately ordering steps under precedence constraints so that the arrangement itself, not just the set of tasks, determines the outcome. |
| Serial Local Optimization Failure | Primary | Stages arranged in series each optimize a local objective while treating their effects on other stages as outside that objective, so individually rational choices compound into an outcome worse than joint optimization. | |
| Simulated Annealing | Primary | — | Probabilistic search escaping local optima. |
| Top-Down Perspectives | Also draws from | — | Centralized control. |
| Traceability | Primary | The infrastructure of bidirectional links that lets any element be followed backward to its origin and forward to its uses, turning opaque processes into auditable, queryable histories. | |
| Trade-offs | Also draws from | — | Balancing competing priorities. |
| Transaction | Also draws from | — | All-or-nothing operations. |
| Translation and Conceptual Bridging | Also draws from | Convert concepts or meanings between incommensurable frameworks. | |
| Two-Sided Matching | Also draws from | — | Forming stable pairings between two sides of a market under each side's preferences. |
| Unevenness Waste | Primary | Variance in arrivals or service through finite shared capacity imposes its own cost — additive to the cost of the mean and rising nonlinearly near the capacity ceiling — so capacity sized to mean demand is not capacity adequate to demand. | |
| Value of Information | Primary | Measure evidence by how much having it before acting is expected to improve the best available decision, relative to acting now and net of the cost of obtaining it. |