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Operational Research Business

Paper type: Essay
Pages: 9 (2230 words)
Categories: Business, Decision Making, Management
Downloads: 13
Views: 396

Introduction

During World War II in England there was a team of British scientists which set out to make decisions pertaining to the optimum utilization of war material. When the war ended, the ideas advanced in military operations and were adapted to improve efficiency and productivity in the civilian sector. Hence the origin of Operations Research O.R. which is a dominant decision making tool today. According to the Operational Research Society of Great Britain, Operational Research is the attack of modern science on complex problems arising in the direction and management of large systems of men, machines, materials and money in industry, business, government and defense.

Its distinctive approach is to develop a scientific model of the system, incorporating measurements of factors such as change and risk, with which to predict and compare the outcomes of alternative decisions, strategies or controls. The purpose is to help management determine its policy and actions scientifically.

CITATION Saa90 l 1033 (Saaty, 1990) argues that O.R. is just a tool of improving quality of answers and further on defines O.R. as the art of giving bad answers to problems which otherwise have worse answers.

As information is crucial to making the best decision, it can be found from the decision-making techniques dealt with in operations research. The objective of decision making is the maximization of profit, minimization of cost, better efficiency, better operational or tactical or strategic planning or scheduling, better pricing, better productivity, better recovery, better throughput, better location, better risk management, or better customer service. The scientific manner involves extensive use of mathematical representations or models of real-life situations. As O.R. is a technique it has various phases which one should follow so as to come up with the best results. The operations researcher first defines the organization’s problem. Next, the operations researcher collects data to estimate the value of parameters that affect the organization’s problem, develops a model which is then verified and uses this model for prediction. Given a model and a set of alternatives, the operations researcher now chooses the alternative that best meets the organization’s objectives which is then implemented. O.R. hence consists of numerous techniques which can be used depending on the situation. A few of the decision making techniques are discussed below and their value elaborated.

Game theory

Basically game theory is the study of how people, companies or nations (referred to as agents or players) determine strategies in different situations in the face of competing strategies acted out by other agents or players. It assumes that agents make rational decisions at all times. According to CITATION Spa11 l 1033 (Spaniel, 2011), it is used for decision making under conflicting situations where there are one or more opponents. Normally a decision maker chooses an optimal decision without reference to the effect that the decision has on other decision makers and vice versa. In many business situations, however, two or more decision makers simultaneously choose an action, and the action chosen by each player affects the rewards earned by the other players. For example, each fast-food company must determine an advertising and pricing policy for its product, and each company’s decision will affect the revenues and profits of other fast-food companies. Game theory is useful for making decisions in cases where two or more decision makers have conflicting interests. Examples in Game Theory include two-person zero-sum game theory in which each player chooses a strategy that enables him to do the best he can, given that his opponent knows the strategy he is following and two-person nonconstant-sum games in which cooperation between the players is not allowed.

The incorporation of game theory by a managing director is advantageous. Firstly it gives insight into several less-known aspects, which arise in situations of conflicting interests. For example, it describes and explains the phenomena of bargaining and coalition-formation. Game theory develops a framework for analyzing decision making in such situations where interdependence of firms is considered. In two-person zero-sum games, it outlines a scientific quantitative technique that can be used by players to arrive at an optimal strategy.

Linear Programming

All businesses are centered on maximizing profit and minimizing cost as such linear programming is one of the most widely used technique in this area. According to CITATION Wil15 l 1033 (Stevenson, 2015) linear programming is a mathematical modelling technique used to determine a level of operational activity in order to achieve an objective, subject to restrictions called constraints. The general structure of linear programming consists of three components of the decision situation: the decision variables, objective function, and constraints from which a model can be formed. Many decisions faced by an operations manager are centred on the best way to achieve the objectives of the ?rm subject to the constraints of the operating environment such as time, labour, energy, materials, or they can be restrictive guidelines, such as engineering speci?cations. A linear programming problem can be solved by using the graphical method or the simplex method depending on the complexity of the problem. However, operations managers are usually interested in more than the optimal solution to a linear programming problem, but also would want to know how sensitive these answers are to input parameter changes for example, what happens if the coefficients of the objective function are not exact, or if they change CITATION Sin16 l 1033 (Singla, 2016). This gave rise to the incorporation of sensitivity analysis in O.R. which is best done by linear programming softwares such as Excel’s Solver. There are also special types of linear programming problems for example transportation and transhipment problems.

To a managing director the linear programming technique has various advantages. The main ones are it indicates how the available resources can be used in the best way hence helping in attaining the optimum use of the productive resources and man. It improves the quality of decisions and reflects the drawbacks of the production process. The necessary modifications of the mathematical solutions are also possible by using Linear Programming. Furthermore it helps in re-evaluation of a basic plan with changing conditions by the use of sensitivity analysis.

Queuing problem

The Queuing Theory, also called as a Waiting Line Theory was proposed by CITATION Erl l 1033 (Erlang, 1990). According to him, the queuing theory applies to those situations where a customer comes to a service station to avail the services and wait for some time (occasionally) before availing it and then leave the system after getting the service.  In queueing theory, queues tend to be modeled by stochastic processes, which are random functions based on probability distributions. Queueing theory models are based on the exponential distribution. The situations where the arrival and departure problems can be seen are uncountable an example being queues formed at the ticket counters. The waiting lines are formed due to the inefficiency of the service system to render immediate services to the customer when they arrive. If the customer has to wait for a long duration, it might lead to the frustration among them, the goodwill might get damaged, and direct cost of idle server- in the case of poor coordination may arise. The demands of a person can only be met by increasing the service capacity, or enhancing the efficiency of the existing elements in the service systems. But however, adding too much capacity may be a costly affair as it may lead to the increased idle time on the part of the server in case of a few or no customers. Also, the setup cost would be too high. Therefore, a manager has to decide the optimal level of service which is neither too high nor too low. Arrival process, service system and queue structure should be kept in mind while designing the queuing system. Thus, the ultimate goal of the queuing theory is to achieve an economic balance between the cost of rendering services and the cost associated with the waiting time. Sequencing Theory is related to Waiting Line Theory. It is applicable when the facilities are fixed, but the order of servicing may be controlled. The scheduling of service or sequencing of jobs is done to minimize the relevant costs. For example, aircrafts waiting for landing clearances.To a managerial post the queuing is important in that a business can develop more efficient queuing systems, processes, pricing mechanisms, staffing solutions, and arrival management strategies to reduce customer wait times and increase the number of customers that can be served.

Network Scheduling-PERT and CPM

Project scheduling is the process of putting together a time line for all the activities in the project CITATION Woo07 l 1033 (Woolf, 2007). It involves examining the interdependencies of all of the activities, and coordinating all the tasks to ensure a smooth transition from the beginning to the end of the project. The Critical path method is a pictorial representation of the project that is useful for identifying the overall length of time that a project will take. It also demonstrates which activities are necessary to complete the project and those that are not as critical. In this technique, the project is represented pictorially as a network, where the nodes represent activities and the duration of an activity is represented by lines or arcs in between nodes. The duration of each activity is estimated based on industry knowledge. Before constructing a diagram, the activities need to be identified, as does the sequencing of these events. The program evaluation and review technique (PERT) is typically applied to more complex projects. Again, a network diagram is used. The activities and their duration are represented pictorially as a network in the same manner as the critical path method. However, unlike the critical path method, PERT allows for flexibility in the period of time to complete a task. Just like the critical path method the activities and their duration are defined. However, the duration is determined with a formula. Gantt charts are a pictorial representation of the phases and activities of a project, and they are typically applied to plans in a setting in which there is little variation among the projects.

It forms the basis for all planning and predicting and help management decide how to use its resources to achieve time and cost goals. A manager will be able to deliver a project on time and hence avert conflicts. Network scheduling provides visibility and enable management to control programs. In addition it helps management evaluate alternatives by answering such questions as how time delays will influence project completion, where slack exists between elements.

Simulation

According to CITATION Ste01 l 1033 (Stewart, 2001) simulation is the process of designing a model of a real system and conducting experiments with this model for the purpose of understanding the behaviour of the system and/or evaluating various strategies for the operation of the system. Purposes of simulation include gaining insight into the operation of a system without disturbing the actual system, developing operating or resource policies to improve system performance, testing new concepts and/or systems before implementation.

The simulation technique is of great benefit to a manager. There is interaction of random events for example random occurrence of machine breakdowns and also non-standard distributions that is simulation gives one the flexibility to describe events and timings as they occur in real life. It is a communication tool (visualisation, animation). It also allows one to clearly describe his/her proposal to others and is able to show the behavior of a system (how the system develops over time) rather than just the end result. Furthermore it makes one think, simulation provides a vehicle for a discussion about all aspects of a process. Most simulation packages have some optimisation add-ons, once a valid simulation model exists it can also be used for optimization. Basic concept of simulation is easy to comprehend and hence easier to justify to customer. It requires fewer simplifying assumptions and hence captures more of the true characteristic of the system under study. Simulation allows gaining of insight into how a modelled system actually works and understanding of which variables are most important to performance.

Summary

Concluding, operations research plays a very crucial role in the decision making process of any business. Although there are some limitations brought by some of the techniques, overall the advantages are greater. Therefore, for one to succeed in business formal education and experience is needed but operations research is an added advantage skill which results in a good decision making at the company. It helps to minimise costs, maximise profit, ensures efficient control, good co-ordination and management, better systems and others. It can also be used in almost every discipline which includes finance, engineering, marketing, production management and others.

BIBLIOGRAPHY

  1. Erlang, A., 1990. Operations research book. 2nd ed. Boston: PWS-Kent Publishing.
  2. Heizer, J., Render, B. & Munson , C., 2017. Operations Management: Sustainability and Supply Chain Management. 12th ed. New Yoke: Pearson.
  3. Ravindan, A. R., 2009. Operations Research Applications. New York: CRC Press.
  4. Saaty, T., 1990. Decision Making for Leaders. California: RWS Publications, 4922 Ellsworth Ave, Pittsburgh.
  5. Singla, S., 2016. Operational Research: A Study of Decision Making Process. JMEST, May, 3(5), pp. 5336-5337.
  6. Spaniel, W., 2011. Game Theory 101: The Complete Textbook. United Kingdom: amazon.co.uk.
  7. Stevenson, W. J., 2015. Operations Management. 12th ed. New York: McGraw-Hill Education.
  8. Stewart, R., 2001. Simulation: The Practice of Model Development and Use. 1st ed. New York: McGraw-Hill Education.
  9. Woolf, M., 2007. Faster Construction Projects with CPM Scheduling. New York: CRC Press

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Operational Research Business. (2019, Nov 24). Retrieved from https://studymoose.com/operational-research-business-essay

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