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OPERATIONS RESEARCH

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Introduction

Operations research (OR) is an analytical method of problem-solving and decision-making that is useful in the management of organizations. In operations research, problems are broken down into basic components and then solved in defined steps by mathematical analysis.

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Major sub-disciplines

  • Computing and information technologies
  • Financial Engineering
  • Manufacturing, service science, and supply chain management
  • Policy modeling and public sector work
  • Revenuue management
  • Transportation

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  • Applications are abundant such as in airlines, manufacturing companies, service organizations, military branches, and government. The range of problems and issues to which it has contributed insights and solutions is vast. It includes:
  • Scheduling (of airline, trains, buses ets.)
  • Assignment (assigning crew to flights, trains or buses; employees to projrcts; commitmen and dispatch of power generation facilities)
  • Facility location (deciding mot appropriate location for new facilities such as warehouse; factory or fire station)
  • Hydraulic & Piping Engineering (managing flow of water from reservoirs)
  • Health Services (information and supply chain management)
  • Game Theory (indentifying, understanding; developing strategies adopted by companies)
  • Urban Design
  • Computer Network Engineering (packet routing; timing; analysis)
  • Telecom & Data Communication Engineering (packet routing; timing; analysis)

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  • Analytical methods used in OR include mathematical logic, simulation, network analysis, queuing theory, broken down into three steps.
  • A set of potential solutions to a problem is developed. (This set may be large.)
  • The alternatives derived in the first step are analyzed and reduced to a small set of solutions most likely to prove workable.
  • The alternatives derived in the second step are subjected to simulated implementation and, if possible, tested out in real-world situations. In this final step, psychology and management science often play important roles.

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  • Operation research has bee existed as a science since 1930’s when it began in a systematic way

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  • But as a formal discipline operational research originated by the efforts of military planner during World War II

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  • In the decade after World war II the techniques began to be applied more widely I problems of business, finances, logistics, industries and societies.

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  • Industrial research

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PROBLEM SOLVING AND DECISION MAKING

  • 7 Steps of Problem solving

(First 5 steps are the process of decision making)

1. Identify and define the problem.

2. Determine the set of alternative solutions.

3. Determine the criteria dor evaluating the alternatives.

4. Evaluate the alternatatives.

5. Choose an alternative.

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6. Implement the chosen alternative.

7. Evaluate the results.

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1. Identify and define the problem.

  • “Right solution” can not be obtained the “wrong problem.”

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  • The first and most important stage of the work is defining the problem well.

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  • This phase helps examine the problem at hand quantitatively.

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2. Determine the set of alternative solutions

  • Development of the functional mathematical relationships that describe-

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  • Decision variables

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  • Objective function

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  • Constraints of the problem

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  • Non negativity condition

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3. Determaine the criteria for ovaluating the alternatives.

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  • A good solution must be measurable. easy to implement and sustainable.

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  • To determine effectiveness of propossed solution two designs are used.

(a) quasi-experimental design.

comparison of situations before and after the solution

(b) true experiment.

comparison of outcome between experimental and control groups.

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4. Evaluate the allternatives

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  • This phase obtains an optimal solution for the model by various techniques.

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  • Various Techniques/Methods;

1. Linear programming Problem (LPP)

2. Transportation Problem (TP)

3. Assignment Problem (AP)

4. Simulation

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6. Implementation

  • A solution to a problem usually implies changes for some individuals in the organization.

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  • Implementation of the solution obtained from a validated model is a reliable solution to the real-life problems.