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Operations Research

Operations research is mainly concerned with the use of analytical methods to create the better decision making. It is mainly used to control and manage the operations in an organization. In execution management, it is used to solve the problem in scientific way. It refers to the decision theory which uses scientific logic and mathematical logic.

Operations research is mainly responsible to improve decision making by using sophisticated analytical techniques. Sometimes, it is also known as management science and operations research. Operation research used in the area of business analytics, decision support, logistics planning, evaluation of advertising, etc. it is used to manage the organization system in industry  by using scientific methods.

Operation Research comes with a diverse range of its tools. Operation research used various Operations researcher used the various tools for performing the different-different tasks, such as define maxima of the profits and performance and minima of the cost, risks and loses. These tools are mathematical optimization tool, statistical analysis and mathematical modeling tools.

Operation Research deals with the several topics, such as Linear Programming problems, Duality theorem, Kuhn Tucker conditions, Wolfe’s and Beale’s algorithms, Decision-making under uncertainty and risk, Non-linear programming, Economic order quantity (EOQ) formula, etc.

To perform a task, Operations Research follows a specific strategy which involves the following steps:

  • Problem definition
  • Information gathering
  • Formulation of model
  • Simulation of model
  • Validation of model
  • Output analysis
  • Implementation and then monitoring

Some of the Major Software that involved in the Operations research are as follows:

  • SAS/OR® Software: this software comes with solution and analytic methods which helps user to recognize the best answers of the problems.
  • GLPK: it stands for Gnu Linear Programming kit which is mainly used for solving the problems of LP, MIP and many others.
  • SimPy: it is a discrete event simulation language enables user to perform the simulation analysis.

Various models that involved in Operation research are Physical Models, Descriptive Models, Symbolic Models, Static Models, Deterministic Models, Dynamic Models, Analytical Models, Normative Models, Predictive Models, Probabilistic Models. Some of the Operation Research techniques are:

  • Optimization: used for choosing the best feasible option by comparing the several options.
  • Computer Simulation: enables user to test the ideas for enhancement.
  • Problem Structuring: it is used by stakeholders in that situations where they need to take complex decisions.
  • Probability and Statistics: with the help of this, user can measure the risk and mine the data to determine the valuable connections in business analytics.

PERT and CPM are known as the popular statistical tools that plays an important role in business field where these are used to manage the project. But in many cases, they both are different with each other. PERT stands for project management technique used to manage the undefined tasks of the projects and CPM stands for Critical Path Method used for managed the well defined tasks of the project. PERT involves the probabilistic model while CPM involves the Deterministic model. PERT is suitable for estimate the high precision time while CPM is suitable for estimate the reasonable time.

Moreover, Integer programming problem refers to a program in which all of the variables are limited in extent to be integers, so it is called pure integer programming problem. In various cases, IP problem refers to the ILP (Integer Linear Programming) problem.  Representation of IP problem:

LP + totally integrated variables = IP

In IP problems, if all the variables are not integer only some of the variables are integer then it is termed as mixed Integer Programming Problem. In some cases, where integer variables are limited extent to 0 but it comes up 1 then this case is termed as pure binary integer programming problems. Various types of common technique take place in the IP problems. These techniques are:

  • Cutting planes: this technique mitigates the search space and adds some constraints to the problem.
  • Heuristics: this is a searching technique which search for integer-feasible solutions
  • Branch and bound: it is designed for solving the combinatorial and mathematical optimization.

NLP refers to a process which is used to solve the optimization problems that are not linear. It comprises of general constraints, variable bounds and objective function. Convex and concave function plays an imperative role in the exploration of NLP. Let us suppose a situation: if there are two given functions, concave and convex and user prove this and also finds an extremum, then a user can be sure that he has found a global extremum. Two types of NLP’s are:

  • Constrained NLP’s: if NLP’s include constraints, then it is known as constrained NLP’s.
  • Unconstrained NLP’s: If NLP’s come without constraints, then it is termed as unconstrained NLP’s

Goal programming is broadly used in OR as it is able to handle the criteria of multiple decisions. Generally, it is used to solve the decision making problems. Model of Goal programming is suitable for planning and managing the decisions, so it can be used to solving the problems of production planning.

Furthermore, various concepts that fall under the Operation Research Subjects are Dual simple method, Queuing system, Markov queuing models, Replacement problems, Queueing models, Sequencing and scheduling problems, and many more. This filed involves the advanced concepts also. Some of the advanced concepts of OR are:

  • Game Theory
  • Extended NLP of Convex Programming
  • Simulation Models
  • Industrial Queuing Processes
  • Network Programming
  • Sequencing Model
  • Dynamics Programming
  • Quadratic Simplex Method

As we know now, Operation Research is a vast field and it consists a broad arrange of topics on which writing an assignment can be difficult for students. To help the students, our experts provide the best assignment and excellent assistance on Operation Research subject. Customer satisfaction is our utmost priority and our experts write the assignment according to the customer requirements. We are trustworthy as we provide the assignment all over the world. So, choose us without hesitation. Some of the benefits that you can get by choosing us:

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Operations Research
  • Foundation mathematics and statistics, Linear Programming, LP and allocation of resources, LP definition, Linearity requirement, Maximization Then Minimization problems., Graphical LP Minimization solution, Introduction, S, implex method definition, formulating the, Simplex model., Linear Programming – Simplex Method for Maximizing., Simplex maximizing example for similar limitations,
  • Mixed limitations, mixed constraints, Minimization, example for similar limitations., Sensitivity Analysis: Changes in Objective Function, Changes in RHS, The Transportation Model, Solution Methods:, Feasible Solution: The Northwest Method, The Lowest, Cost Method, Optimal Solution: The Stepping Stone Method, Modified; Distribution (MODI) Method., The Assignment Model:- Basic Assumptions, Solution Methods:-Different Combinations Method,, Short-Cut Method, MSPT:- The Dijkestra algorithm, and Floyd’s Algorithm
  • Linear Programming: The Graphical Method, Sensitivity Analysis and Computer Solution*, Modelling and Optimisation Software, Post-Optimality Analysis, Simplex Method, Integer Programming, Branch and Bound for IP, Modelling Discrete Optimisation, Modelling Network Optimisation, Nonlinear Programming, Optimization Models, Linear Programming, Linear Programming Models, Graphical Solution, Simplex Algorithm and Goal Programming, Sensitivity Analysis and Duality, Transportation Models, Network Models and Algorithms, Integer Programming, Modeling with integer variables, Branch and Bound Methods, Dynamic Programming, Queueing Models, Nonlinear Programming, Nonlinear Models, KKT conditions, Constrained/Unconstrained optimization, Algorithms

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