operations-research-algorithm-developer
/operations-research-algorithm-developer
Formulate and implement operations research optimization models—LP, MIP/QP, constraint programming, network flows, assignment, VRP, scheduling, resource allocation, inventory/production planning; heuristics and metaheuristics; sensitivity and infeasibility diagnosis; solver integration (OR-Tools, Gurobi, CPLEX, HiGHS, PuLP, Pyomo); production OR APIs (timeouts, warm starts). Use for operations research, OR engineer, optimization model, linear programming, mixed integer programming, MIP, VRP, vehicle routing, scheduling optimization, OR-Tools, Gurobi, constraint programming, resource allocation
- Author
- rade-nugroho ↗
- Repository
- agentic-enteprises-skill ↗
- Licence
- MIT
- Last repository change
- 20.05.2026
Assessment and security
- Files in this package
- 7
- Scripts
- 0
- HTML comments
- 0
- URLs in SKILL.md
- 0
No signals detected. Repository changed on 20.05.2026, without references to retired models or APIs.
MIT, open: use and modify while retaining author attribution.
What it does and when to use it
Formulate and implement operations research optimization models—LP, MIP/QP, constraint programming, network flows, assignment, VRP, scheduling, resource allocation, inventory/production planning; heuristics and metaheuristics; sensitivity and infeasibility diagnosis; solver integration (OR-Tools, Gurobi, CPLEX, HiGHS, PuLP, Pyomo); production OR APIs (timeouts, warm starts). Use for operations research, OR engineer, optimization model, linear programming, mixed integer programming, MIP, VRP, vehicle routing, scheduling optimization, OR-Tools, Gurobi, constraint programming, resource allocation
Original author description
Formulate and implement operations research optimization models—LP, MIP/QP, constraint programming, network flows, assignment, VRP, scheduling, resource allocation, inventory/production planning; heuristics and metaheuristics; sensitivity and infeasibility diagnosis; solver integration (OR-Tools, Gurobi, CPLEX, HiGHS, PuLP, Pyomo); production OR APIs (timeouts, warm starts). Use for operations research, OR engineer, optimization model, linear programming, mixed integer programming, MIP, VRP, vehicle routing, scheduling optimization, OR-Tools, Gurobi, constraint programming, resource allocation
How it works
- When to Use
- When NOT to Use
- Related skills
- Core Workflows
- Outputs
- Principles
- When to load references
SKILL.md preview
--- name: operations-research-algorithm-developer description: | Formulate and implement operations research optimization models—LP, MIP/QP, constraint programming, network flows, assignment, VRP, scheduling, resource allocation, inventory/production planning; heuristics and metaheuristics; sensitivity and infeasibility diagnosis; solver integration (OR-Tools, Gurobi, CPLEX, HiGHS, PuLP, Pyomo); production OR APIs (timeouts, warm starts). Use for operations research, OR engineer, optimization model, linear programming, mixed integer programming, MIP, VRP, vehicle routing, scheduling optimization, OR-Tools, Gurobi, constraint programming, resource allocation optimization, infeasible model, metaheuristic—not ML prediction (data-scientist), SCM strategy without optimization math (supply-chain-manager), WMS features (wms-developer), simulation platforms (simulation-software-engineer), generic backend (senior-software-engineer), dbt/warehouse (analytics-data-engineer). --- # Operations Research Algorithm Developer ## When to Use - Frame a **decision problem** as an optimization model—objectives, decisions, constraints, parameters, uncertainty - Build **LP, MIP, QP, or constraint programming** formulations for planning and allocation - Model **network flows**, **assignment**, **routing (VRP)**, **scheduling**, and **resource allocation** - Design **inventory and production planning** models (lot sizing, capacity, multi-period) - Select **exact vs heuristic** methods—branch-and-bound, column generation, decomposition, metaheuristics - Run **sensitivity analysis**, **infeasibility diagnosis**, and **benchmarking** (optimality gap, runtime) - Integrate **solvers** conceptually—OR-Tools, Gurobi, CPLEX, HiGHS, PuLP, Pyomo—and production patterns - Prepare **input data**, validate units, and enforce **constraint modeling discipline** - **Productionize** OR services—APIs, timeouts, warm starts, incremental solves, solution pools ## When NOT to Use - **General ML predictive modeling**, feature engineering, A/B tests, or MLOps → `data-scientist` - **Supply chain strategy**, RFQ, supplier scorecards, or inventory policy without optimization math → `supply-chain-manager` - **WMS workflows**—waves, pick paths, RF scanning, ERP/WMS integration → `wms-developer` - **Simulation platform software**—physics engines, SIL/HIL rigs, deterministic replay frameworks → `simulation-software-engineer` - **Generic backend**, CRUD APIs, or cloud microservices without OR models → `senior-software-engineer` - **Analytics warehouse**, dbt marts, dimensional modeling, BI semantic layers → `analytics-data-engineer` - **Formal proof obligations** or certified assurance cases → `software-assurance-formal-methods-specialist` ## Related skills | Need | Skill | |---|---| | ML prediction, experimentation, MLOps | `data-scientist` | | SCM sourcing, forecast process, supplier QBRs | `supply-chain-manager` | | Warehouse management application logic | `wms-developer` | | DES/physics sim platforms, digital twins | `simulation-software-engineer` | | Enterprise application and API engineering | `senior-software-engineer` | | dbt, warehouse modeling, BI pipelines | `analytics-data-engineer` | | Executive dashboards and KPI storytelling | `bi-analyst` | | Service SLOs and production incident response | `site-reliability-engineer` | ## Core Workflows ### 1. Scope and problem class Clarify decision horizon, granularity, optimality requirements, and handoffs to product/engineering. **See `references/or_algorithm_developer_scope.md`.** ### 2. Formulation and data Define sets, parameters, variables, objective, constraints; validate data and units. **See `references/problem_formulation_and_data.md`.** ### 3. Linear and integer optimization LP/MIP/QP structure, big-M discipline, tightening, decomposition hooks. **See `references/linear_and_integer_optimization.md`.** ### 4. Routing, scheduling, and networks VRP variants, job-shop and resource scheduling, min-cost flow and assignment patterns. **See `references/routing_scheduling_and_networks.md`.** ### 5. Heuristics and metaheuristics When to leave exact solvers; construction, local search, GA/SA/TS; solution quality metrics. **See `references/heuristics_and_metaheuristics.md`.** ### 6. Solver integration and production Solver choice, model lifecycle, APIs, timeouts, warm starts, monitoring, and failure modes. **See `references/solver_integration_and_production.md`.** ## Outputs - **Problem formulation brief**—decisions, objective, hard vs soft constraints, assumptions - **Mathematical model**—notation, formulation, linearization notes, parameter catalog - **Data specification**—required inputs, validation rules, unit checks, scenario keys - **Solution report**—objective, gap, runtime, binding constraints, sensitivity highlights - **Infeasibility / IIS summary**—conflicting constraint groups and remediation options - **Implementation outline**—solver stack, API contract, timeout and fallback policy - **Benchmark table**—instances, gap %, time, memory, method comparison ## Principles - **Formulate before coding**—write the math (even briefly) before choosing a solver API - **Separate data from model**—parameters drive constraints; avoid hard-coding scenario logic in solver calls - **Prefer tight formulations**—fewer binaries, tighter bounds, and valid inequalities over brute force - **Measure optimality**—report gap, bounds, and time limits; never imply optimality without proof - **Diagnose infeasibility systematically**—IIS, elastic filters, or constraint relaxation ladders - **Production OR needs SLOs**—timeouts, warm starts, and feasible incumbent policies are part of the design - **Route non-OR work to peers**—ML, WMS features, and sim platforms are not substitutes for correct OR scope ## When to load references | Topic | Reference | |---|---| | Role scope, boundaries, RACI | `references/or_algorithm_developer_scope.md` | | Sets, parameters, validation | `references/problem_formulation_and_data.md` | | LP, MIP, QP, tightening | `references/linear_and_integer_optimization.md` | | VRP, scheduling, networks | `references/routing_scheduling_and_networks.md` | | Heuristics, metaheuristics | `references/heuristics_and_metaheuristics.md` | | Solvers, APIs, production | `references/solver_integration_and_production.md` |
Files in this package (7)
- SKILL.md 6 KB
- references/heuristics_and_metaheuristics.md 3 KB
- references/linear_and_integer_optimization.md 3 KB
- references/or_algorithm_developer_scope.md 4 KB
- references/problem_formulation_and_data.md 4 KB
- references/routing_scheduling_and_networks.md 3 KB
- references/solver_integration_and_production.md 4 KB
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