Introduction to Operational Research

Introduction to Operational Research

• Operational research (OR) is a problem-solving approach using mathematical and analytical methods to improve efficiency, effectiveness, and decision-making in organizations.
• OR aims to optimize outcomes by identifying the best course of action from various alternatives.
• Key characteristics of OR include:
  • Problem-focused approach, not product-focused.
  • Interdisciplinary nature, involving expertise from various fields.
  • Application of scientific methods to real-world problems.
  • Data-driven decision-making supported by mathematical modeling.
  • Emphasis on finding optimal solutions.

Key Areas of Operational Research

• OR encompasses a broad range of techniques and applications, including:
  • Linear programming: optimizing systems with linear relationships between variables.
  • Integer programming: extending linear programming for integer-valued variables.
  • Network analysis: scheduling and resource allocation in projects using graph-based models.
  • Queuing theory: systems with waiting lines and servers, like call centers or production lines.
  • Simulation: modeling complex systems to analyze behavior and outcomes under various conditions.
  • Decision theory: making optimal decisions under uncertainty and risk.
  • Inventory control: managing stock levels to minimize holding and shortage costs.
  • Forecasting: anticipating future trends using techniques like exponential smoothing and time-series analysis.
  • Project management: planning and scheduling projects using techniques like the critical path method (CPM) and program evaluation and review technique (PERT).
  • Optimization models: finding the best possible solution within constraints and objectives.

Applications of Operational Research

• OR is used across various industries and sectors, such as:
  • Manufacturing: optimizing production schedules, inventory management, and resource allocation.
  • Healthcare: scheduling appointments, managing waiting times, and optimizing resource allocation in hospitals.
  • Transportation: optimizing delivery routes, managing traffic flow, and planning transportation systems.
  • Finance: portfolio optimization, risk management, and investment analysis.
  • Retail: inventory control, pricing strategies, and store layout optimization.

Stages in Operational Research

• A typical OR study involves the following stages:
  • Defining the problem: clearly stating the objective and constraints.
  • Constructing a mathematical model: representing the problem mathematically.
  • Deriving a solution: finding an optimal solution based on the model.
  • Testing the solution: evaluating the solution's validity and feasibility.
  • Implementing the solution: putting the solution into practice.
  • Monitoring and evaluating the results: assessing effectiveness and making adjustments.

Data Collection and Analysis

• Gathering relevant data is crucial for OR studies.
• Sources of data include historical records, surveys, experiments, and external databases.
• Descriptive and inferential statistics are used for data analysis and interpretation.

Model Building

• OR models range from simple linear equations to complex simulations.
• The model should accurately represent the key aspects of the problem.
• Model validity and reliability are crucial for accurate interpretation.

Evaluation and Decision-Making

• Evaluating solutions, considering the problem's context and complexities, is essential.
• Factors like feasibility, cost, and practicality are key considerations.
• The final solution is determined based on predefined criteria and objectives.