Operations Research Lab
20+ OR models across optimization, scheduling, inventory, queueing, simulation, and decision analysis. No file upload needed — enter your parameters directly and get results with step-by-step workings and formulas.
Overview
Operations Research Lab is organized into 6 sections by problem type. Unlike other labs, no data upload is required — every model works from parameters you enter directly. Results include the optimal solution, the full formula derivation, and interpretive notes.
Mathematical Optimization
LP, ILP, GP, Network Optimization
Assignment & Scheduling
Hungarian, CPM/PERT, Job-Shop
Inventory & Supply Chain
EOQ, Safety Stock, Facility Location
Stochastic Models
Markov Chains, Queueing, Reliability
Simulation & Risk
Monte Carlo, Discrete Event, Scenario
Decision Analytics
Decision Trees, AHP, MCDM
No file upload needed
All OR models work from parameters you type in — objective coefficients, constraint matrices, demand rates, arrival/service rates, criteria weights, etc. There is no CSV upload step.
How it works
Select a model
Browse the 6 sections in the sidebar — each section’s overview lists its models. Click any model to open it.
Build the problem
Set it up with the on-page builder — for LP, choose Maximize / Minimize, type the objective coefficients, add or toggle constraints, and pick the inequality. A Live Preview on the right renders the full model in math notation as you type. In a hurry? Load a built-in example (Production Mix, Diet Problem, Workforce, Portfolio).
Solve and read the result
Click Solve and the result loads instantly: an Optimal Solution strip — decision variables, Z*, iterations, and binding count — and, for optimization models, a Constraint Binding Analysis (slack, utilization, shadow price π) and an Objective Contribution Breakdown. Reset clears the form; export as CSV or Word, or ask AI Chat to explain.
AI Chat — ask anything about your result
Once you solve a model, a circular toggle button appears in the results panel. Click it to open AI Chat — the AI already knows the model, your parameters, and the result, so you can ask follow-up questions without re-explaining.
Interpret the solution
Ask what the optimal values mean in practical terms — not just the number, but what it implies for your decision.
Explain shadow prices
Ask what it would cost to relax a constraint by one unit, and whether it's worth doing.
Sensitivity questions
Ask "how much can demand change before the reorder point shifts?" or "what if the arrival rate doubles?"
Draft a summary
Request a plain-language paragraph explaining the result, ready to include in a report or presentation.
AI Chat panel
the circular toggle button + AI Chat open on a result
Model catalog
Mathematical Optimization
Find the optimal solution to a constrained objective — maximize profit, minimize cost.
Linear Programming (LP)
Simplex method with sensitivity analysis, dual problem, and graphical method for 2-variable problems.
Integer Programming (ILP)
Binary and mixed-integer LP solved with Branch & Bound.
Goal Programming
Multi-objective optimization — weighted, lexicographic, or Chebyshev.
Network Optimization
Shortest path, max flow, min-cost flow, and minimum spanning tree.
Assignment & Scheduling
Assign resources to tasks and sequence jobs to minimize time or cost.
Assignment Problems
Hungarian algorithm for balanced and unbalanced assignment. Supports multi-objective variants.
Scheduling
Job-shop, flow-shop, shift scheduling, and nurse rostering.
Project Management
CPM / PERT critical path, Gantt chart, and resource leveling.
Inventory & Supply Chain
Optimize stock levels, reorder points, and supply chain structure.
EOQ / EPQ
Economic Order Quantity and Economic Production Quantity with cost breakdown and reorder point.
Safety Stock & ROP
Safety stock calculation under demand uncertainty. Reorder point with service level targets.
Supply Chain Optimization
Multi-echelon SC, bullwhip effect, and vendor selection.
Facility Location
P-Median, set covering, capacitated FLP, and gravity model.
Stochastic Models
Model systems driven by probability — queues, chains, and reliability.
Markov Chains
Absorbing chains, steady-state probabilities, transition matrix analysis (DTMC / CTMC).
Queueing Theory
M/M/1, M/M/c, M/G/1 queues — waiting time, utilization, and queue length formulas.
Reliability Analysis
Series/parallel systems, fault tree analysis, MTBF / MTTR, and availability.
Simulation & Risk
Quantify uncertainty through simulation and scenario testing.
Monte Carlo Simulation
Custom distributions, convergence analysis, VaR / CVaR, and sensitivity.
Discrete Event Simulation
Process modeling, resource utilization, throughput analysis, and bottleneck detection.
Scenario Analysis
Scenario comparison, tornado chart, break-even analysis, and stress testing.
Decision Analytics
Make structured decisions under uncertainty with multiple criteria.
Decision Trees
Expected value, utility theory, sensitivity analysis, and Bayesian updating.
AHP
Analytic Hierarchy Process — pairwise comparison matrix, consistency ratio, and priority vector.
MCDM
TOPSIS, VIKOR, ELECTRE, and weighted sum model for multi-criteria ranking.
Where to start
Maximize profit or minimize cost
Linear Programming
Assign workers or sequence jobs
Assignment & Scheduling
How much to order and when
EOQ / Safety Stock
Model a waiting line or queue
Queueing Theory (M/M/1)
Simulate uncertainty in outcomes
Monte Carlo Simulation
Choose between options with trade-offs
AHP / MCDM