Operational research (OR) uses analytical techniques to improve decision-making and efficiency. It encompasses problem-solving methods applied to optimize performance. OR analyzes systems through mathematical modeling, simulation, and other techniques. It aims to make the best use of resources by carefully planning and analyzing processes. Examples of OR applications include scheduling, facility planning, forecasting, yield management, and defense logistics. The field originated from military planning in World War II and has since expanded to business, industry, and public policy problems.

1. OPERATION RESEARCH AND
OPTIMIZATION TECHNIQUES
Operation Research
Introduction
B.Vivekanandam
Lincoln University College

2. WHAT IS OPERATIONAL RESEARCH?
 Operations research, or operational research in British
usage.
 Operational Research (OR) is the use of advanced
analytical techniques to improve decision making.
 Operational research (OR) encompasses a wide range of
problem-solving techniques and methods applied in the
pursuit of improved decision-making and efficiency.
 It is sometimes known as Operations Research,
Management Science or Industrial Engineering.

3. WHAT IS OPERATIONAL RESEARCH?
 Analytical methods used in OR include
mathematical logic, simulation, network analysis,
queuing theory , and game theory . The process
can be broadly broken down into three steps.

4. WHY IS OR NEEDED?
 Because it makes sense to make the best use of
available resources.
 Today’s global markets and instant communications
mean that customers expect high-quality products and
services when they need them, where they need them.
 Organizations, whether public or private, need to
provide these products and services as effectively and
efficiently as possible.
 This requires careful planning and analysis – the
hallmarks of good OR.
 This is usually based on process modeling, analysis of
options or business analytics.

5. EXAMPLES OF OR IN ACTION
 Scheduling: of aircrews and the fleet for airlines, of
vehicles in supply chains, of orders in a factory and of
operating theatres in a hospital.
 Facility planning: computer simulations of airports for
the rapid and safe processing of travelers, improving
appointments systems for medical practice.
 Planning and forecasting: identifying possible future
developments in telecommunications, deciding how
much capacity is needed in a holiday business.

6. EXAMPLES OF OR IN ACTION
 Yield management: setting the prices of airline
seats and hotel rooms to reflect changing demand
and the risk of no shows.
 Credit scoring: deciding which customers offer the
best prospects for credit companies.
 Marketing: evaluating the value of sale promotions,
developing customer profiles and computing the
life-time value of a customer.
 Defense and peace keeping: finding ways to
deploy troops rapidly.

7. SOME OR METHODS AND TECHNIQUES
 Computer simulation: allowing you to try out
approaches and test ideas for improvement.
 Optimization: narrowing your choices to the very best
when there are so many feasible options that comparing
them one by one is difficult.
 Probability and statistics: helping you measure risk,
mine data to find valuable connections and insights in
business analytics, test conclusions, and make reliable
forecasts.
 Problem structuring: helpful when complex decisions
are needed in situations with many stakeholders and
competing interests.

8. MAJOR SUB DISCIPLINES IN MODERN
OPERATIONAL RESEARCH
 Computing and information technologies
 Environment, energy, and natural resources
 Financial engineering
 Manufacturing, service sciences, and supply chain
management
 Marketing Engineering
 Policy modeling and public sector work
 Revenue management
 Simulation
 Stochastic models
 Transportation.

9. HISTORY
 operational research originated in the efforts of military
planners during World War II. In the decades after the war,
the techniques began to be applied more widely to
problems in business, industry and society.

10. DEFINITIONS
 Operations Research (OR) is the study of mathematical
models for complex organizational systems.
 Optimization is a branch of OR which uses Mathematical
techniques such as linear and nonlinear programming to
derive values for system variables that will optimize
performance.

11. Deterministic Models Stochastic Models
• Linear Programming • Discrete-Time Markov Chains
• Network Optimization • Continuous-Time Markov Chains
• Integer Programming • Queuing
• Nonlinear Programming • Decision Analysis
OPERATIONS RESEARCH MODELS

12. STEPS IN OR STUDY

13. JOBS
 People with skills in OR hold jobs in decision
support, business analytics, marketing analysis and
logistics planning – as well as jobs with OR in the
title.