Operations Research - An Analytic Tool for a Researcher.ppt
29 July 2022 1
Operations Research –
Analytic Tool for a Researcher
(29-07-2020)
Dr. L.P. Raj Kumar
Department of Mathematics
Kakatiya University – Warangal – TS, INDIA
29 July 2022 2
Introduction to Operations Research
Problems which can be analyzed by Operations Research
Important Tools used in Operations Analysis
Opportunities for doing Operations Research
Applications of Operations Research
Few examples on Stochastic Processes
8 Traits for 21st Century Teachers
Why Personality Development
7 Ways to use Technology for Purposes
5 Best Practices for a Good Researcher
Contents
Introduction
In its recent years of organized development, Operations
Research has solved successfully many cases of
research for military, the government and industry.
With the explosion of population and consequent
shortage of food, every country is facing the problem of
optimum allocation of land for various crops in
accordance with climatic conditions and available
facilities.
The problem of optimal distribution of water from a
resource like a canal for irrigation purposes is faced by
developing country. Hence a good amount of scientific
work can be done in this direction.
Introduction
In the field of Industrial Engineering, there is a claim of
problems, starting from the procurement of material to
the dispatch of finished products. Management is
always interested in optimizing profits.
The O.R. approach is equally useful for the economists,
administrators, planners, irrigation or agricultural
experts and statisticians etc.
Operation research approach helps in operation
management. Operation management can be defined
as the management of systems for providing goods or
services, and is concerned with the design and
operation of systems for the manufacture, transport,
supply or service.
Introduction
Thus the operation management is concerned with the
optimum utilization of resources i.e. effective utilization
of resources with minimum loss, under utilization or
waste. In other words, it is concerned with the
satisfactory customer service and optimum resource
utilization. Inputs for an operating system may be
material, machine and human resource.
Problems which can be analyzed by Operations Research
1. Finance, Budgeting and Investment:
i. Cash flow analysis, long range capital requirement,
investment portfolios, dividend policies,
ii. Claim procedure, and
iii. Credit policies.
2. Marketing:
i. Product selection, competitive actions,
ii. Number of salesmen, frequencies of calling on, and
iii. Advertising strategies with respect to cost and time.
Problems which can be analyzed by Operations Research
3. Purchasing:
i. Buying policies, varying prices,
ii. Determination of quantities and timing of purchases,
iii. Bidding policies,
iv. Replacement policies, and
v. Exploitation of new material resources.
4. Production Management:
i. Physical distribution: Location and size of warehouses,
distribution centers and retail outlets, distribution
policies.
ii. Facilities Planning: Number and location of factories,
warehouses etc. Loading and unloading facilities.
iii. Manufacturing: Production scheduling and sequencing
stabilization of production, employment, layoffs, and
optimum product mix.
iv. Maintenance policies, crew size.
v. Project scheduling and allocation of resources.
5. Personnel Management:
i. Mixes of age and skills,
ii. Recruiting policies, and
iii. Job assignments.
6. Research and Development:
i. Areas of concentration for R&D.
ii. Reliability and alternate decisions.
iii. Determination of time-cost trade off and control of
development projects.
Important Tools used in Operations Analysis
1. Mathematical programming
(a) Linear programming
(b) Nonlinear programming
(c) Dynamic programming
2. Game theory
3. Probabilistic models
(a) Queuing
(b) Inventory control
(c) Monte Carlo method
4. Transportation models
(special cases of linear programming)
Important Tools used in Operations Analysis
5. Simulation techniques
6. Time-network analysis
(a) PERT
(b) CPM
7. Sequential analysis
8. Other methods
(a) Input-output analysis
(b) Capital budgeting
(c) Forecasting
Opportunities for doing Operations Research
With the current job market trend- the scope of OR is extremely
huge. People with OR degrees working in finance, data analytics,
industry optimization, supply chain management, business
analytics, FinTech and consulting services are seen. Basically, any
kind of decision making requires usage of operations research
tools. Decision making in today’s world requires quantification
and mathematical modeling. OR techniques help you do exactly
that.
1. Financial Engineering - stock prediction, time series analysis,
stochastic finance, trading strategies, algorithmic trading, risk
management, corporate finance and investment analysis. You
need models to determine stock anomalies, you use
mathematical modeling and programming to make your
computational power loaded laptop to do that for you.
Opportunities for doing Operations Research
2. Data Analytics and Business — Business development strategies,
data innovation, financial data, data wrangling, data mining and
so on. You have a large amount of data on customer satisfaction
and you want to use that data to form improved strategies to
reduce customer churn rate. You use modeling techniques that
determine important factors and use predictive analytics to
come with information that helps us develop strategies.
3. Consulting - Management consulting, strategy and operations. A
company hires a team of consultant to help them with a new
project on oil drilling and solar panel installations. You use
analytics and research on optimization of the supply chain side
of the business maybe. Or on the operations end of the
business.
4. Operations Research Analysts: Operations research analysts use
advanced mathematical and analytical methods to help solve
complex issues.
Opportunities for doing Operations Research
2. Data Analytics and Business — Business development strategies,
data innovation, financial data, data wrangling, data mining and
so on. You have a large amount of data on customer satisfaction
and you want to use that data to form improved strategies to
reduce customer churn rate. You use modeling techniques that
determine important factors and use predictive analytics to
come with information that helps us develop strategies.
3. Consulting - Management consulting, strategy and operations. A
company hires a team of consultant to help them with a new
project on oil drilling and solar panel installations. You use
analytics and research on optimization of the supply chain side
of the business maybe. Or on the operations end of the
business.
4. Operations Research Analysts: Operations research analysts use
advanced mathematical and analytical methods to help solve
complex issues.
Assignment Problems
• Timetabling Problem. Timetabling is described as an assignment of events to a
limited number of timeslots and rooms subject to prescribed constraints. In
reality, allocation of resources at a specified time is indeed necessary.
• Examination Timetabling Problem. The examination timetabling problem (ETP)
is defined as an assignment of a set of examinations to a set of timeslots while
simultaneously satisfying several problem constraints.
• Course timetabling Problems. The Course timetabling Problems refers to the
process of assigning courses, rooms, students, and lecturers to a fixed time
period, typically a working week, while satisfying a given set of constraints.
• School Timetabling Problem. The school timetabling problem (STP) is about
generating school timetable that usually follows a cycle every week for all
classes, in which the objective is to avoid teachers from attending two classes
at the same time.
• Student-Project Allocation Problem. The student project allocation problem
(SPAP) is related to assigning a person to a particular project or cases based on
preference or interest of student and lecturer.
• New Student Allocation Problem. The new student allocation problem (NSAP)
is a clustering problem in allocating new students to their corresponding class
with minimum intelligence gap by sorting method: a group of new students
with similar ranking and assigned into the same class.
In Biology
In biotechnology and medicine, biology most tasks lie in
the wide fields of prediction and process optimization.
Biologists like to concentrate on the modeling and
forecasting of genetic processes, and on the
optimization of cell metabolism with regard to
maximizing production efficiency.
In Pharmacy
The pharmaceutical industry is one with activities being under taken on
a massive scale, involving expertise of several other fields and sectors.
When their products, which mainly include chemical drugs, are
discovered, developed, made and marketed, it involves the use of
operation research in several ways to make the processes more
efficient. Operation research is mainly used to make this industry
more profitable, as well as to make their activities easier and faster.
Applications of operation research to the pharmaceutical industry,
not limited to supply chain management, inventory management,
financial management and project management, to extent are such
methods adopted, and can be applied to a small pharmaceutical
company or large pharmaceutical company that currently outsources
most of its operations.
In Oil, Gas and Fuel applications
These problems present a number of specific features such as
vehicles with capacitated compartments and sometimes
the presence of flow meters to control the delivered
quantity. The latter feature implies that sometimes the
content of the same compartment can be used to satisfy
the demands of several customers, whereas when there is
no flow meter, the compartment must be completely
emptied in a single customer tank. Cleaning operations may
be needed between the loading of different products using
the same compartment. These problems are generally
solved over long-term planning horizons and incorporate
mixed inventory and routing decisions.
In Retail Applications
Retail involves the sales of goods and the provision of services
to end-users. In this section we list applications dealing
with a number of final products, and in various sectors such
as supermarkets and consultancy services. These
applications generally involve time windows and loading
constraints.
In Waste Collection and Management
Waste collection is essential to the proper functioning of any
collectivity. A variant of the problem deals with hazardous
waste management in which collection, transportation,
treatment and disposal of hazardous materials are
involved. These problems are characterized by loading and
un- loading constraints, time windows, and inter-arrival
time constraints at customer points.
In Mail and Small Package Delivery
This section reviews applications ranging from mail delivery to
the delivery of Internet orders, touching many variants of
the classical VRP such as those involving time windows and
pickups and deliveries.
In Food distribution
Food distribution has its own characteristics, constraints and
challenges such as product quality, health and safety. The
products often have a limited shelf-life, so that distribution
operations must take into account temperature, humidity
and time-in-transit considerations, as well as many other
product-related constraints. These focuses on the
challenges of food safety, quality and sustainability. These
must include strategic network design, tactical net- work
planning and operational transportation planning.
Few examples on Stochastic Processes
1. A Brand – Switching Model for Consumer Behavior
Suppose there are three brands on sale, a, B, and C. The customer
either buy the same brand for a few months or either change
their brands every now and then. There is also a strong
possibility that when a superior brand is introduced some of the
old brands will be left with only few customers. To gage
consumer behavior a sample survey of the stores is necessary
( it would be more useful, if such a survey is conducted before
and after the introduction of a new brand).
In such a survey, conducted over a period of time, suppose the
estimates obtained for the consumer brand-switching behavior
are as follows : Out of those who brought brand A in one month,
during the next month 60% buy A again, 30% switch to B, and
10% switch to brand C. For brand B and C, these figures are, B to
A 50%, B to B 30%, B to C 20%, and C to A 40% to B 40%, C to C
20%.
A Brand – Switching Model for Consumer Behavior
If we are interested in the number of people who buy a certain
brand of coffee, then that number could be represented as a
stochastic process. The behavior of the consumer can also be
considered as a stochastic process which could enter three
different states A, B, or C.
Some of the questions that arise are : What is the expected number
of moths that a customer stays with one brand?. What are the
mean and variance of the number using a particular brand after a
certain number of months?. Which is the product preferred most
by the customers on the long run? etc.
As per the survey, the distribution is as follows,
A B C
A 60 30 10
B 50 30 20
C 40 20 20
A Brand – Switching Model for Consumer Behavior
Similar type of problems may be
1. Mobile Networking(Customers always try to change their
network from one brand to another. Airtel, Jio, Vodaphone etc.)
2. Wheat/ Rice Brand (Consumers always try to change their
Rice/Wheat brand from one brand to another. Masoori, Vijaya
Masoori, Soya Masoori etc.)
3. Milk Product(Consumers always try to change their Mild Products
from one product to another
A B C
A 60 30 10
B 50 30 20
C 40 20 20
2. A Queueing Problem
• A bus taking students back and forth between the hostel
complex and the college arrives at the college several times
during the day. The bus has the capacity to seat K persons. If
there are K or less waiting persons when the bus arrives, it
departs with available number. If there are more than K waiting,
the driver allows the first K to board and the remaining persons
must wait for the next bus. The university administrators would
like to know at each time period during the day, how many
students are left behind when a bus departs.
• The number waiting at the bus stop is a stochastic process
dependent on the arrival process( say with some probability
distribution),. Some desirable characteristics of the system are
reduction in the number waiting at any time, minimizing the
time a student has to wait for a ride, minimizing the operational
cost etc.
2. A Queueing Problem
Similar type of problems may be
1. Traffic Signals(Vehicles waiting during the busy period).
2. Hostel Mess(Student waiting for lunch/dinner at a
limited room)
3. Multispecialty Hospitals(Patients waiting for treatment)
3. Population Growth Problems
It is more realistic to consider the growth of a population is
stochastic rather than deterministic. The external factors that
influence the growth of animals, such as weather conditions,
disease, availability of food, etc., are too varied and uncertain
for deterministic models. When these factors are identified and
accounted for the population size at any time can be considered
as a stochastic process. In problems of this nature, we would not
only be interested in the behavior of the process, but also in
using such information in the control of the growth or decline of
the population. ( A lack of such action could result in the species
becoming extinct.
3. Population Growth Problems
Similar type of problems may be
1. Increase in Corona effected patients.(Patients
admitted into hospitals due to Corona).
2. Sheep/Cattle growth at a village.(Growth of
cattle)
3. Poultry Farm (Growth of Hens)
4. Recovery, Replace, and Death Due to a Disease
The process of recovery, replace and death is the case of some
major disease such as cancer is governed by several random
causes, and therefore stochastic process models have been
found useful in the study of hospital data related to such cases.
For instance, three different state of patients can be identified:
i) the initial state of being under treatment. ii) the state of
recovery and the state of being lost after recovery
4. Recovery, Replace, and Death Due to a Disease
Similar type of problems may be
1. Corona effected patients admitted into hospitals.
2. Sheep/Cattle at a village.
5. A Time - Sharing Computer System
Jobs of varied length come to a computing center from various
sources. The number of jobs arriving, as well as their length can
be said to follow certain disr=tributions. Under these conditions
the number of jobs waiting at any time and the time a job has to
spend in the system can be represented by stochastic. Under a
strictly “First Come First Serve” policy, there is a good chance of
a long job delaying a much more important shorter job over a
long period time. For the efficient operation of the system, in
addition minimizing the number of jobs waiting and total delay,
it is necessary to adopt a different service policy. A round-robin
policy in which the service is performed on a single job only for a
certain length of time, say 3 or 5 sec, and those jobs which need
more service are put back in the queue, is one of the common
practices adopted under these conditions.
5. A Time - Sharing Computer System
Similar type of problems may be
1. People waiting at the DTP Center for service.
2. Customers waiting at a Xerox Center for service.
3. People waiting at Internet Center for service.
Why Personality Development
Soft Skills vs Hard skills ?
Importance of Skills in 21st century
Lifelong learner
For an Academician
Knowledge Up gradation
Vision & Plan
Positive Attitude.
Learn from Young Generation
Submit and Surrenderance to Knowledge
5 Best Practices for a Good Researcher
• Practice Writing : Simple, clear and direct.
• Practice Creating your own Documents: Use any word
processor.
• Practice Showing : Don’t tell your reader, instead show
what you have done.
• Practice Edit, edit, edit: Once you finish a piece of
writing, let it be revised/edited to make it better.
• Practice to understand a classic work : Practicing to
understand what makes a great writing/work is one of
the best ways to grow your own skills.
29 July 2022
You are the Designer of Yourself
Teachers and Others are only Tools
29 July 2022 42
Best Wishes
&
May God Bless You
Dr. L.P. Raj Kumar
Department of Mathematics
Kakatiya University – Warangal – TS, INDIA
Email : lp_raj8@yahoo.com
Mobile : 98491 33398