MEE407- Operations Research I
COURSE PARTICULARS
Course Code: MEE 407
Course Title: Operations Research I
No. of Units: 3
Course Duration: Two hour of theory and One hour of Tutorials per week for 15 weeks.
Status: Compulsory
Course Email Address: mee@futa.edu.ng
Course Webpage: http://www.mee.futa.edu.ng/courseschedule.php?coursecode=MEE%20204
Prerequisite: NIL
COURSE INSTRUCTORS
Dr. B. Kareem
Room 28, School of Engineering and Engineering Technology (SEET) Building,
Dept. of Mechanical Engineering,
Federal University of Technology, Akure, Nigeria.
Phone: +2348033737251
Email: bkareem@futa.edu.ng; karbil2002@yahoo.com
COURSE DESCRIPTION
This course deals majorly with linear optimisation techniques. This is a course covering the
linear quantitative management tools which are applicable in management of industries. This is
primarily designed for mechanical engineering students to expand their knowledge in the areas
of industrial engineering and management. In the course, students will be taught how linear
programming can be formulated, solved using standard methods (simplex algorithms, primal and
dual), and how the optimal solution can be interpreted. The course will impart useful
management skills of providing solution to transportation/transhipment problems using
established algorithms (shortest path, maximum flow, etc.). The students will be taught on how
the network analysis can be applied to project planning and control. The subject matter will be
extended for students to be able to have real-life application of conventional project planning
algorithms (Critical Path Method (CPM) and Program Evaluation and Review Technique
(PERT) to industrial project development. Students will be taught how to make appropriate
engineering decisions in the areas of resources (material, manpower, and machinery) planning
and management using operations research tools/algorithms (dynamic programming, integer
programming, game theory, etc.). Hands-on training of students in the areas of application of
computer software in solving many of the stated algorithms will be carried out. Topics to be
covered include linear programming-formulation, simplex method: simplex algorithm for
solving linear programming problems-primal and duality, interpreting optimal solution. Concept
of duality. Transportation/transhipment problem: shortest path, minimum flow, minimum
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spanning tree, minimum cost network flow, sensitivity analysis. Network analysis: shortest route
problem. Minimum/maximum flow problem. CPM and PERT with application to project
planning and control. Dynamic programming; deterministic and stochastic: shortest path,
knaspsack, job planning, and production management; Game theory; and Integer programming
using branch and bound technique. Applications of operation research software packages.
COURSE OBJECTIVES
The objectives of this course are to:
 introduce students to the use of operation research tools for various industrial and
operations management activities; and
 provide students with opportunities to develop basic industrial and academic
management skills with respect to application of mathematical programming such as
linear, dynamic, and transhipment algorithms.
COURSE LEARNING OUTCOMES / COMPETENCIES
Upon successful completion of this course, the student will be able to:
(Knowledge based)
 explain the basic elements and the areas of application of operations research tools in
organisations;
 classify and explain the linear models formulation, solutions and optimality interpretation
procedures;
 understand purpose and functions of each of the linear-based operations research tools
in industrial sectors;
 understand the application of familiar software to execute some basic algorithms of the
models; and
 understand how the models can be practically applied to selected organisations in
planning and management of resources including material, manpower and machinery.
(Skills)
 use the linear operations research tools to:
o plan and optimise the use of material, manpower, and machinery in an
organisation;
o
evolve an effective transportation system for the organisation;
o prevent delays in organisational project implementation through effective
application of CPM and PERT techniques;
o enhance effective decision making in the organisation through practical
application of dynamic programming and game theory algorithms to the
complex organisational situations related to material, man and machine;
 develop a software for the implementation of the emerging algorithms;
 perform a practical case studies reports using the appropriate algorithms;
 produce a practical reports on the optimisation of industrial resources- material, man and
machines; and
 perform analytical computations of selected theoretical and practical examples.
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GRADING SYSTEM FOR THE COURSE
This course will be graded as follows:
Class Attendance
10%
Assignments
20%
Test(s)
10%
Final Examination
60%
TOTAL
100%
GENERAL INSTRUCTIONS
Attendance: It is expected that every student will be in class for lectures and also participate in
all tutorials. Attendance records will be kept and used to determine each person’s qualification to
sit for the final examination. In case of illness or other unavoidable cause of absence, the student
must communicate as soon as possible with any of the instructors/lecturers, indicating the reason
for the absence.
Academic Integrity: Violations of academic integrity, including dishonesty in assignments,
examinations, or other academic performances are prohibited. You are not allowed to make
copies of another person’s work and submit it as your own; that is plagiarism. All cases of
academic dishonesty will be reported to the University Management for appropriate sanctions in
accordance with the guidelines for handling students’ misconduct as spelt out in the Students’
Handbook.
Assignments and Group Work: Students are expected to submit assignments as scheduled;
failure to submit an assignment as at when due will earn it zero. Only under extenuating
circumstances, for which a student has notified any of the instructors/lecturers in advance, will
late submission of assignments be permitted.
Code of Conduct in Lecture Rooms and Laboratories: Students should turn off their cell phones
during lectures. Students are prohibited from engaging in other activities (such as texting,
watching videos, etc.) during lectures. Food and drinks are not permitted in the lecture room.
READING LIST
1
Gordon G. (1992). System Simulation. 2nd Edition , Prentice-Hall of India, New Delhi. 324p.
3,4
Kareem, B. (2012). Transportation model under predictable safety and security threats,
Transport- Strategical and operational Issues (Monograph), Agnieszka Stachowiak (ed.),
Chap. 2,pp. 21-32, Poznan University of Technology Publishing House, Poland.
3,4
Kareem, B. (2012). Transportation under deplorable road safety and security maintenance,
Jour. Research in Logistics & Production, Vol. 2, No.4, pp. 367-376, Poland.
3
4
Kareem B. and Aderoba A.A. (2004). Application of Linear Programming Model to Manpower
Planning, Proceedings of the 2004 National Engineering Conference of NSE, pp. 164-171.
4
Kareem B. (2010). Application of LP -Transportation Model for Effective Allocation of
Petroleum Resources for Industrial Construction in Nigeria, Proceedings of the Second
International Conference on Construction In Developing Countries (ICCIDC–II)
“Advancing and Integrating Construction Education, Research & Practice” August 3-5,
2010, Cairo, Egypt, pp. 510-515.
3,4
Kareem, B. and Akande, S.O. (2012). Knowledge-graded manpower planning model for the
manufacturing industry, Inter. Jour. of Engrg. Innov. and Manag, Vol 2, pp 49-58.
3,4
Kareem B. and Aderoba A.A. (2008) Linear Programming based Effective Maintenance and
Manpower Planning Strategy: A Case Study, International Journal of the Computer,
Internet and Management, vol. 16, no. 2. pp. 26-34.
3,4
Kareem B. (2009). A Dynamic Model for Sequential Expansion in Building, Machinery and
Manpower Based on Gradual Funding, Proceedings of Construction in the 21st Century
“Collaboration and Integration in Engineering, Management and Technology “, Antalya,
Turkey, pp. 228-233.
1,4
1
Payne A.C.; Chelsom J.V. and Reavill L.R.P. (1996). Management for Engineers. John Wiley
& Sons Ltd, England. 592p.
Taha H.A. (2008). Operations research: An Introduction. 8th Edition , Macmillan Inc. USA.
876p.
4,5
Verma A.P. (2011). Operations research. 6th Edition. S.K. Kataria & Sons, New Delhi. 1183p.
Legend
1- Available in the University Library
2- Available in Departmental/School Libraries
3- Available on the Internet.
4- Available as Personal Collection
5- Available in local bookshops.
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COURSE OUTLINE
Week
1
2&3
4&5
6
7&8
9 & 10
Topic
Remarks
Introduction and Course Overview
Linear programming-formulation:
 Variable,
 Objective and
 Constraints
During this first class, students are
expected to understand basic elements
of linear programming based operation
research tools. Their expectation from
the course will be documented.
Linear programming model solution
 Simple method
 Simplex algorithm for solving linear
programming problems
 Primal and duality
 Interpreting optimal solution.
 Concept of duality.
 Sensitivity analysis
Transportation/transhipment problem:
 Initial basic solution, Northwest corner
rule,Vogel’s approximation method,
Least cost method
 The Modified Distribution method MODI
or U-V method of solution
 Other
areas
of
application
of
transportation models
Students will be taught on how this
model can be applied to real-life
problems. Illustrations and work
examples will be carried out
Students will be taught on how this
model can be applied to real-life
problems. Illustrations and work
examples will be carried out
Network analysis:
Students will be taught on how this
model can be applied to real-life
 Shortest route problem.
problems. Illustrations and work
 Minimum/maximum flow problem.
 CPM and PERT with application to examples will be carried out.
project planning and control.
Dynamic programming;
Students will be taught on how this
 Deterministic and stochastic
model can be applied to real-life
 Shortest path and knaspsack
problems. Illustrations and work
 Job planning, and
examples will be carried out.
 Production management.
MID-SEMESTER TEST
Students will be taught on how this
model can be applied to real-life
problem. Illustrations and work
examples will be carried out.
Game theory
 Pure strategy
 Saddle point
 Mixed strategy
5
11 & 12
13 & 14
15
Integer programming
using branch and bound technique.
Students will be taught on how this
model can be applied to real-life
problems. Illustrations and work
examples will be carried out.
Application of operations research computer software
to solving the stated problems.
 Visual basic
 Fortran language
 C++
 Java
 Visual basic.net
Students will be taught on how to
apply familiar software packages
(Visual basic, Java, C++, etc.) to
the model algorithms. A case study
will be carried out and report
written and presented in groups.
REVISION
This is the week preceding the final
examination. At this time,
evaluation will be done to assess
how far the students’ expectations
for the course have been met.
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