Queuing Theory and Inventory Models Quiz

Study Notes

Operations Research Techniques

Operations researchers emphasize the development and use of techniques like linear programming, game theory, decision theory, queuing theory, inventory models, and simulation.
Other common tools include non-linear programming, integer programming, dynamic programming, sequencing theory, Markov process, network scheduling (PERT/CPM), symbolic Model, information theory, and value theory.

Linear Programming

Linear programming is a constrained optimization technique that optimizes some criterion within some constraints.
The objective function (profit, loss, or return on investment) and constraints are linear.
Different methods are available to solve linear programming.

Game Theory

Game theory is used for making decisions under conflicting situations where there are one or more players/opponents.
The motive of the players is dichotomized, and the success of one player tends to be at the cost of other players.

Decision Theory

Decision theory is concerned with making decisions under conditions of complete certainty about the future outcomes and under conditions where some probability can be made about what will happen in the future.

Queuing Theory

Queuing theory is used in situations where a queue is formed (e.g., customers waiting for service, aircrafts waiting for landing, jobs waiting for processing in the computer system).
The objective is to minimize the cost of waiting without increasing the cost of servicing.

Inventory Models

Inventory models make decisions that minimize total inventory cost.
The model successfully reduces the total cost of purchasing, carrying, and out of stock inventory.

Simulation

Simulation is a procedure that studies a problem by creating a model of the process involved in the problem and then through a series of organized trials and error solutions attempts to determine the best solution.
Simulation is used when actual experimentation is not feasible or a solution of the model is not possible.

Non-linear Programming

Non-linear programming is used when the objective function and the constraints are not linear in nature.
Linear relationships may be applied to approximate non-linear constraints but are limited to some range.

Dynamic Programming

Dynamic programming is a method of analyzing multistage decision processes.
Each elementary decision depends on those preceding decisions and external factors.

Integer Programming

If one or more variables of the problem take integral values only, then dynamic programming is used.
Examples include the number of motors in an organization, the number of passengers in an aircraft, or the number of generators in a power generating plant.

Markov Process

Markov process permits predicting changes over time, given information about the behavior of a system.
It is used in decision making in situations where the various states are defined.

Network Scheduling

Network scheduling is used extensively to plan, schedule, and monitor large projects.
The aim is to minimize trouble spots (such as delays, interruptions, production bottlenecks, etc.) by identifying critical factors.

Operations Research Development Process

Step I: Observe the problem environment, which includes conferences, site visits, research, and observations.
Step II: Analyze and define the problem, including problem definition, objectives, uses, and limitations of the O.R. study.
Step III: Develop a model, which is a representation of some abstract or real situation.
Step IV: Select appropriate data input, which includes internal/external data analysis, fact analysis, and collection of opinions and use of computer data banks.
Step V: Provide a solution and test its reasonableness, which involves getting a solution with the help of the model and input data, testing the model, and finding any limitations.

Description

Test your knowledge on Queuing Theory, Inventory Models, and Simulation techniques used in decision-making processes. Learn about optimizing waiting costs, inventory management, and total cost reduction strategies.