Unit 1: Operations Research & Decision-Making Environments
Operations Research
Operations Research (OR) is a scientific approach to decision-making that uses mathematical models, statistical analysis, and optimization techniques to find the best possible solutions to complex business problems.
Uses of Operations Research
Operations Research is used in various sectors to improve decision-making, resource allocation, and operational efficiency.
a) Optimizing Resources: OR helps businesses make the best use of limited resources like money, manpower, machines, materials, and time.
b) Improving Decision-Making: OR provides a structured and logical way of analyzing problems to support better decision-making.
c) Reducing Costs: By finding optimal solutions (like shortest route, minimum cost, or least time), OR helps in reducing unnecessary expenses.
d) Enhancing Productivity:It suggests efficient ways to carry out operations, which increases the productivity of the organization.
e) Handling Complex Situations: OR models simplify complex problems, making them easier to understand and solve.
Scope of Operations Research
Operations Research is not limited to any one area. It is applicable across various business and functional domains:
Applications of OR in Managerial Decision-Making
a) Linear Programming (LP): Used for optimizing production and resource allocation problems. Example: How to produce different products with limited raw materials to maximize profit.
b) Transportation and Assignment Models: Solves problems related to transporting goods or assigning jobs in the most cost-efficient way. Example: Assigning workers to tasks where they are most productive.
c) Inventory Control: Helps determine when and how much inventory to order. Example: EOQ (Economic Order Quantity) helps minimize ordering and holding costs.
d) Queuing Theory: Analyzes waiting lines to improve service efficiency. Example: Managing customer service desks, hospital patient queues.
e) Simulation: Used when the real system is too complex to model mathematically. Example: Simulating customer behavior in a shopping mall.
f) Game Theory: Helps in competitive decision-making scenarios. Example: Pricing strategies in a competitive market.
g) Decision Theory: Assists in choosing the best course of action under uncertain conditions. Example: Launching a new product in an unknown market.
h) Network Analysis (PERT/CPM): Helps in project planning and scheduling. Example: Planning the construction of a building or launching a product.
In Short, Operations Research is a powerful tool for managers. It allows them to make informed, data-driven decisions that improve efficiency, productivity, and profitability. It is widely used in strategic planning, operations, logistics, and problem-solving across industries.
Decision-Making Environments
Decision-making is the process of selecting the best course of action from different alternatives. The nature of the decision-making process depends on the amount of information available and the predictability of outcomes. Based on this, there are three types of decision-making environments:
1. Decision-Making Under Certainty
In this environment, the decision-maker has complete and accurate information about all alternatives, and the outcome of each alternative is known with certainty.
🔹 Features:
- Only one outcome for each decision.
- No ambiguity or doubt.
- Easy to analyze and make decisions.
🔹 Example: A company knows that if it invests ₹1,00,000 in a project, it will surely get ₹1,20,000 in return. Since the outcome is guaranteed, the decision is made under certainty.
2. Decision-Making Under Uncertainty
In this case, the decision-maker does not know the probabilities of the outcomes and has very little or no information about future events.
🔹 Features:
- Multiple outcomes are possible, but probabilities are unknown.
- Difficult to predict the result.
- Requires assumptions or personal judgment.
🔹 Example: A new entrepreneur wants to launch a new product in a completely unknown market. They have no data or past experience to rely on. The decision is made under uncertainty.
🔹 Common techniques used:
- Maximin (pessimistic)
- Maximax (optimistic)
- Minimax Regret (minimizing regret)
- Laplace criterion (based on equal probabilities)
3. Decision-Making Under Risk
Here, the decision-maker knows the possible outcomes and the probability of each outcome happening. So, decisions are made based on expected values or averages.
🔹 Features
- Multiple outcomes are possible.
- Probabilities of outcomes are known or can be estimated.
- More realistic and practical than certainty.
🔹 Example: A company is planning to launch a product and based on market research, there is a:
- 60% chance of high demand,
- 30% chance of medium demand,
- 10% chance of low demand.
Based on these probabilities, the company can calculate expected profits and make the best decision.
🔹 Common techniques used:
- Expected Value (EV) Analysis
- Decision Trees
- Risk Analysis Models
- Decision Tree Approach
What is a Decision Tree?
A Decision Tree is a graphical representation of possible solutions to a decision-making problem. It helps in selecting the best alternative by showing various decision paths, chance events, and outcomes, along with their associated probabilities and expected values.
🧩 Key Components of a Decision Tree
🛠️ Steps to Build a Decision Tree
- Define the problem and objectives.
- Identify all possible alternatives (decisions).
- Identify possible outcomes for each decision.
- Assign probabilities to each outcome.
- Determine payoffs (profits or losses) for each outcome.
- Calculate Expected Monetary Values (EMV).
- Choose the decision path with the highest EMV.
📊 Formula: Expected Monetary Value (EMV)
Applications of Decision Tree in Business and Management
Simple Example of a Decision Tree: Suppose a company is considering launching a new product. There are two options:
- Launch
- High demand (60% chance): Profit = ₹50,000
- Low demand (40% chance): Loss = ₹20,000
- Do Not Launch
- No profit or loss (₹0)
➤ EMV of Launch = (0.6 × ₹50,000) + (0.4 × -₹20,000)
= ₹30,000 - ₹8,000 = ₹22,000
Since EMV of Do Not Launch = ₹0, the company should launch the product.
🧠Benefits of Decision Tree Approach
- Easy to visualize and interpret
- Helps in making structured decisions
- Supports decisions under risk and uncertainty
- Useful for quantitative analysis
- Assists in calculating expected returns