Operations Research Hub

Operations Research (OR) is the discipline of applying advanced analytical methods to help make better decisions. This hub organizes Wikantik's OR content, from foundational mathematical programming to specialized applications in logistics, warehouse automation, and revenue management.

Foundations and History

The origins and core principles of the discipline.

• History of Operations Research — From military roots to a pillar of modern industrial engineering
• Applied Math Survey — The broader mathematical context in which OR operates
• Linear Programming Foundations — The bedrock of optimization: linear objectives and constraints

Optimization Techniques

Algorithms and frameworks for finding the best solutions.

• Integer and Combinatorial Optimization — Handling discrete variables and complex search spaces
• Constraint Programming — Solving combinatorial problems by specifying constraints
• Metaheuristic Optimization — General-purpose search strategies: genetic algorithms, simulated annealing, and more
• Numerical Methods — Solving math problems using discrete computer arithmetic

Supply Chain and Logistics

Applying OR to the movement and storage of goods.

• Supply Chain and Logistics Optimization — Overarching frameworks for global trade and distribution
• Optimization in Warehouse Automation — Pathfinding, slotting, and task interleaving in modern fulfillment centers
• Vehicle Routing Problem — Minimizing distance and cost in delivery networks
• Inventory Theory — Mathematical models for when and how much to reorder
• Demand Planning and S&OP — Integrating forecasting with operational planning

Stochastic Models and Systems

Managing uncertainty and time-varying behavior.

• Stochastic Models in OR — Decision-making when outcomes are probabilistic
• Queueing Theory — The study of waiting lines: buffers, latency, and throughput
• Simulation Modeling — Using computational runs to understand complex, non-deterministic systems
• Markov Chain Fundamentals — Modeling state transitions over time

Specialized Industrial Applications

• Production Scheduling and OR — Optimizing manufacturing floor throughput and sequence
• Revenue Management with OR — Dynamic pricing and capacity allocation in travel and retail
• Network Optimization — Designing resilient and efficient communication and physical networks

Adjacent Hubs

• Mathematics Hub — The underlying calculus, algebra, and probability
• ML Hub — Where OR meets data-driven learning
• Data Engineering Hub — Building the pipelines that feed optimization models