What is Operations Research (OR)?
Operations Research (OR) may be defined as the science that aims for the application of analytical and numerical techniques along with information technology to solve organisational problems. There are various definitions of OR in the literature.
Table of Content
- 1 What is Operations Research (OR)?
- 2 Operations Research Definition
- 3 Concept of Operations Research
- 4 History of Operations Research
- 5 Characteristics of Operations Research
- 6 Objectives of Operations Research
- 7 Tools of Operations Research
- 8 Advantages of Operations Research
- 9 Limitations of Operations Research
- 10 Applications and Uses of Operations Research in Management
Operations Research Definition
Some of the well-known operations research definitions are as:
Moarse and Kimbal (1946) defined OR as a scientific method of providing the executive department a quantitative basis for decision-making regarding the operations under their control.
According to Churchman, Ackoff and Arnoff (1957), OR is the application of scientific methods, techniques and tools to operational problems so as to provide those in control of the system an optimum solution to the problem.
McGraw-Hill Science & Technology Encyclopaedia states that OR is the application of scientific methods and techniques to decision-making problems.
Britannica Concise Encyclopaedia defines OR as the application of scientific methods to the management and administration of military, government, commercial, and industrial processes.
Decision-making problems arise when there are two or more alternative courses of action, each resulting in a different outcome. The goal of OR is to help select the alternative that will maximise the use of available resources and lead to the best possible outcome.
In this article, we introduce the topic of operation research that will allow students to gain an insight into the basic concepts of operations research. This will give them a better understanding of the upcoming chapters.
Concept of Operations Research
Decision-making is not a simple task in today’s socio-economic environment. Complex problems such as transportation, queuing, etc., are routinely presented and dealt with at the operational level. Moreover, higher attention is now being paid to a wide range of tactical and strategic problems.
Decision makers cannot afford to take decisions by simply taking their personal experiences or intuitions into account. Decisions made in the absence of suitable information can have seri- ous consequences. Being able to apply quantitative methods to deci- sion-making is, therefore, vital to decision-makers.
OR is a field of applied mathematics that makes use of analytical tools and mathematical models to solve problems and aid the management in decision-making. OR is an approach that allows decision makers to compare all possible courses of action, understand the likely outcomes and test the sensitivity of the solution to modifications or errors.
OR helps in making informed decisions, allocating optimal resource and improving the performance of systems. According to Ackoff (1965), the development (rather than the history) of OR as a science consists of the development of its methods, concepts, and techniques.
OR is neither a method nor a technique; it is or is becoming a science and as such is defined by a combination of the phenomena it studies.
History of Operations Research
The beginning of OR as a formal discipline can be traced back to 1937 when A.P. Rowe, Superintendent of the Bawdsey Research Station in the British Royal Air Force, sought British scientists to assist military leaders in the use of the recently developed radar system to detect enemy aircraft.
A few years later, the British Army and the Royal Navy also incorporated OR, again for assistance with the radar system. All three of Britain’s military services had set up formal OR teams by 1942. Similar developments took place in other countries (of which the most significant are those of the United States, in terms of further development of the discipline).
Once World War II ended, several British operations researchers relocated to government and industry. By the 1950s, the United States government and industry also incorporated OR programmes. In India, it was in 1949 when an Operation Research unit was set up at Regional Research Laboratory, Hyderabad, that OR came into being.
An OR team was also established at Defense Science Laboratory to resolve inventory, purchase and planning issues. The 1950s saw continual growth in the application of OR methods to non-defence activities in India. In 1953, the Indian Statistical Institute, Calcutta established an OR unit for national planning and survey-related issues. OR also became useful in the Indian Railways to resolve ticketing issues, train scheduling problems and so on.
Since then, OR, as a formal discipline, has expanded continuously in the last 70 years and is widely recognised as a central approach to decision-making in the management of different domains of an organisation.
With accessibility to faster and flexible computing facilities, OR has expanded further and is widely used in industry, finance, logistics, transportation, public health and government. One needsCharacteristics of Operations Research to bear in mind that OR is still a fairly new scientific discipline, despite its rapid evolution. This means that its methodology, tools and techniques, and applications still continue to grow rapidly.
Characteristics of Operations Research
OR aims to find the best possible solution for any problem. Its main goal is to help managers obtain a quantitative basis for decision-making. This results in increased efficiency, more control and better coordination in the organisation when fulfilling the required objectives.
OR is an interdisciplinary field involving mathematics and science. OR uses statistics, algorithms and mathematical modelling to provide the best possible solutions for complex problems. OR basically involves optimising the maxima or minima functions.
For example, a business problem could be the maximisation of profit, performance or yield or it could be related to minimising risk and loss. OR has various characteristics based on the different objectives for which it is used.
The characteristics of operations research (OR) are explained as follows:
OR as a decision-making approach
All organisations are faced with situations where they need to select the best available alterna- tive to solve a problem. OR techniques help managers in obtaining optimal solutions for their problems.
Additionally, OR techniques are also used by managers to understand the problems at hand in a better manner and make effective decisions. It is important to note that OR techniques help in improving the quality of decisions.
OR helps in finding bad answers to problems having worse answers. It means that for many problems, OR may not be able to give perfect replies but can help in improving the quality of decisions.
OR as a scientific approach
OR uses multiple scientific models along with tools and techniques to resolve complex problems while eliminating individual biasness. The scientific method involves observing and defining a problem, formulating and testing the hypothesis and analysing the results of the test. The results of the test determine whether the hypothesis should be accepted or rejected.
OR as an interdisciplinary approach: Since OR focuses on complex organisational problems, it includes expertise from different disciplines such as mathematics, economics, science and engineering. Having different experts ensures that the problem is analysed from different perspectives and alternative strategies are evolved for the selected problem.
Some of the complex problems that can be solved using OR include deciding or choosing optimal dividend policies, investment portfolio management, auditing, balance sheet and cash flow analysis, selection of product mix, marketing and export planning, advertising, media planning and packaging, procurement and exploration, optimal buying decisions, transportation planning, facilities planning, location and site selection, production cost and methods, assembly line, blending, purchasing and inventory control, etc.
OR as a systems approach: In OR, important interactions and their influence on the organisation as a whole are considered for decision-making. OR looks at problems from the perspective of the organisation:
- To determine the potential for enhancing the performance of the system as a whole
- To measure the impact of alterations in variables on the whole system
- To find reasons for the malfunctioning of the system as a whole
OR as a computer-based approach
OR solves business problems using mathematical models, manipulating large amount of data and performing computations on these large data sets. It is almost impossible to do such computations and manipulations manually. Therefore, most OR-based problems are solved using computers.
Objectives of Operations Research
Operations research in an organisation is responsible for managing and operating as efficiently as possible within the given resources and constraints. In case of complex problems as listed in the previous section, normal analysis does not work and in such cases, OR approach helps an organisation in reaching a viable solution.
OR is basically a problem-solving and decision-making tool used by organisations for enhancing their productivity and performance. Apart from this, certain other objectives of OR are as follows:
- Solving operational questions
- Solving queries related to resources’ operations such as human resource scheduling, machine and material scheduling, utilisation of funds, etc.
- Making informed decisions
- Improving the current systems
- Predicting all possible alternative outcomes
- Evaluating risks associated with each alternative
OR is needed for the following reasons:
- If the problem is a recurring one, it may make sense to create a model to make decision-making faster and better. OR provides a readymade model or process in such cases to help create a suitable model.
- OR provides an analytical, logical and quantitative basis to represent the problem
- OR models help in making sound decisions and decreases the risk of flawed decisions
Tools of Operations Research
OR is widely used in industries, businesses, governments, military establishments and agriculture. Most importantly, OR techniques are used by organisations. All the business decision areas, such as planning production and facilities, scheduling projects, minimising procurement costs, and selecting a product mix, which require optimisation of an objective, fall under the domain of operation research. OR uses a variety of tools to solve different business problems.
The most commonly used tools of OR are discussed below:
Organisations use the Linear Programming (LP) technique to determine the optimal solutions that may be defined as either most profitable or least cost solutions. Businesses use LP techniques to assign jobs to machines, select product mix, select advertising media, select an investment portfolio, etc.
Simulation is another important OR tool wherein an expert con- structs a model that replicates a real business scenario. Simulation is extremely useful in cases where actual market testing is risky or impossible due to various reasons such as high expenditure.
It has widely been used in a variety of probabilistic marketing situations. For example, finding the Net Present Value (NPV) distribution of the market introduction of a product.
Statistics allows an organisation to evaluate the risks present in all the domains of the business. It enables an organisation to predict future trends and thus makes informed business decisions. The OR team compares different trade-offs and chooses the best alternative.
For example, statistics is used in solving various real-life problems such as deterministic optimisation. Some of the problems where statistics serve as the primary vehicle for OR include decision theory, optimal strategies for search engine marketing, credit scoring, queuing theory, stochastic programming and inventory management.
The assignment method deals with the issue of how to allocate a fixed number of facilities to different tasks in the most optimal manner. The aim is to minimise the cost/time of completing a number of tasks by a number of agents (person or equipment). For example, assigning method can be used to assign specific workers to specific tasks.
If a problem involves queuing, the Queuing or Waiting Line theory is used. Using this tool, the expected number of people waiting in line, expected waiting time, expected idle time for the server and so on can be calculated. Queuing theory can be used to solve problems related to traffic congestion, repair and maintenance of broken machines, air traffic scheduling and control, scheduling bank counters, etc
Game theory is useful in decision-making in cases where there are one or more opponents (or players) with conflicting interests. Just as in a game, where the success of one person is influenced by the choices made by the opponent, in the game theory, the actions of all the players influence the outcomes.
For example, game theory is used for selecting war strategies and military decisions, bidding at auctions, negotiations, product pricing, stock market decisions, etc.
Non-linear problems are similar to linear problems except that they have at least one non-linear function or constraint. Non-linear models become useful in cases where the objective function of some of the constraints is not linear in nature.
For instance, a non-linear programming is used for making optimal decisions in the production process, optimising fractionated protocols in cancer radiotherapy, training recur- rent neural networks in time series prediction problems, etc.
Dynamic programming models deal with problems in which decisions need to be made over multiple stages in a sequence and the current decisions affect both present and future stages.
For example, dynamic programming is used by Google Maps to find the shortest path between a source and a destination. It is also used in networking to sequentially transfer data from one sender to various receivers.
Goal programming tools allow organisations to handle multiple and incompatible objectives. These models are quite similar to linear programming models with the difference being that goal programming can have multiple objectives whereas linear programs have only one.
For example, goal programming can be applied to corporate budgeting, financial planning, working capital management, financing decisions, commercial bank management, accounting control, etc.
Network scheduling methods are useful in planning, scheduling and monitoring projects of large scales common in construction industry, information technology, etc.
For example, network scheduling is used for assembly line scheduling, inventory planning and control, launching new advertisement campaigns, installing new equipment, controlling projects, etc.
Advantages of Operations Research
The field of OR contains robust tools that can be applied in a variety of fields such as transportation, warehouse, production management, assignment of jobs, etc. The application of OR tools and techniques helps in making the best decisions with the available data.
There are many advantages of OR, as shown in Figure:
OR helps in increasing the productivity of organisations to a huge extent. The use of OR for effective control of operations allows the managers to take informed decisions. Effective and precise decision-making leads to improvement in the productivity of an organisation.
OR tools also help increase the efficiency of various routine tasks in an organisation such as inventory control, workforce-related, business expansion, technology upgrades, installation etc. All these ultimately contribute towards productivity improvement.
Management is responsible for making various important decisions about the organisation. OR tools can be used by the management to find out various alternative solutions to a problem and selecting the best solution. Selection is based on the profits accrued and costs incurred.
OR can be used to synchronise the objectives of different departments which results in achieving the goals of all departments. Managers belonging to different departments become aware of the common objectives of the organisation, which ensures that different departments coordinate towards achievement of the said goals.
For example, OR helps in coordinating the goals of the marketing department with the production department schedule.
Lower failure risk
Using OR tools and techniques, managers can find all the alternative solutions and risks associated with a given problem. Prior information with respect to all the possible risks helps in reducing the risks of failure.
Improved control on the system
Managers can apply OR to take better control of the work since it provides comprehensive information about any given course of action. Since OR informs managers about the expected outcome, they can determine what standards of performance need to be expected from employees.
They can compare the actual performance of the employees with the standard performance and, therefore, control them in a better manner. It also enables managers to prioritise tasks in terms of their importance.
Limitations of Operations Research
There is no doubt with respect to the practical utility and usability of OR and its applications in real life. However, OR also suffers from several limitations as shown in Figure:
High cost is one of the biggest limitations of OR. It not only needs expensive technology to create mathematical equations but also experts to perform simulations. Therefore, while OR does provide effective solutions to a particular problem, it comes with a high cost attached.
Dependence on technology
OR is heavily reliant on technology. Computers are generally needed to model and analyse OR problems. Since technology is quite costly as well as subject to failure, its use is severely restricted.
Reliance on experts
OR requires a team of experts from different fields to perform the assessments. Hiring multiple experts can be costly. In addition, maintaining good communication and coordination among experts and making all experts work together is a critical task.
It is known that OR tools are based on mathematical models that include various information based on quantifiable factors. It means that the efficacy of a solution provided by OR tool depends on quantifiable factors.
However, there are certain important unquantifiable factors that cannot be included in the models. When this happens, solutions can often be inexact, inaccurate and therefore, inefficient.
Applications and Uses of Operations Research in Management
The list of OR applications is notable, given its considerable involvement in various managerial and decision-making processes at several organisational levels. It can be applied in a wide range of industries to help with complex problems in planning, policy-making, scheduling, forecasting, resource allocation, process analysis, etc.
It may be employed by virtually any industry to determine the best solution to any problem. Various human activities that need optimisation of resources can use OR.
The following are some areas where OR may be applied:
Resource distribution in projects
Various OR tools are used to determine which resources are to be allocated to which activities. For instance, OR can help in determining the allocation of ‘n’ number of jobs among two machines. Similarly, OR can also be applied to determine and allocate materials, workforce, time and budget to projects.
Project scheduling, monitoring and control
OR is applied to activities involving scheduling, inventory control, improvement of workflow, elimination of bottlenecks, business process re-engineering, capacity planning and general operational planning.
OR tools such as the Critical Path Method (CPM) and Project Evaluation and Review Technique (PERT) are used for scheduling the different activities involved in a project. In addition, these tools are also used for continuous monitoring and control of the project.
Production and facilities planning
OR can be applied for activities involving site selection, factory size, facility planning, inventory forecasts, calculation of economic order quantities, computing reorder levels, maintenance policies, replacement policies, manpower planning, and assembly line scheduling, etc. All the important decisions and planning work related to facilities, manufacturing and maintenance can be completed using OR tools.
Application of OR can be done in budget allocation for advertising, choice of advertising media and product launch timing. For instance, how should a company allocate its budget for advertising a newly launched product on two TV channels, TV1 and TV2 within a given budget. A company may also use OR techniques to find out how many units of each product in a product mix should be produced to maximise demand.
OR also finds application in manpower planning, scheduling of training programs, wage administration, etc.
Finance and accounting: The application of OR in finance is concerned with effective capital planning, cash flow analysis, capital budgeting, credit policies, investment analysis and decisions, establishing costs for by-products and developing standard costs, portfolio management, risk management, etc.
Supply chain management
The application of OR in Supply Chain Management involves decision-making regarding the transportation of goods for the purpose of manufacturing and distribution. This further involves the selection of the shortest optimal routes so that the goods can be transported to maximum locations at minimum costs.