SDST3606 Business logistics (6 credits) Academic Year 2025
Offering Department SCDS (Department of Statistics and Actuarial Science) Quota ---
Course Co-ordinator Dr O T K Choi, SCDS (Department of Statistics and Actuarial Science) < ochoi@hku.hk >
Teachers Involved (Dr O T K Choi,Statistics & Actuarial Science)
Course Objectives Modern business corporations are increasingly using logistics as a management tool, for example, in capital budgeting problems, production planning, scheduling, transportations and deciding location for a new factory.  This course addresses the business applications of logistics.
Course Contents & Topics In this course, students will apply the analytical skills with aid of computer techniques in solving the business logistic problems. Topics include optimization techniques applied in allocation of resources, financial planning, transportation, assignment, inventory control and queuing problems.
Course Learning Outcomes
On successful completion of this course, students should be able to:

CLO 1 solve linear programming with Graphical approach, Simplex method and hands-on Excel Solving function
CLO 2 set up and solve network flow problems using least-cost approach, MODI method and Vogel's approximation.
CLO 3 understand decision theory and its applications
CLO 4 evaluate the cost and effectiveness of service systems
Pre-requisites
(and Co-requisites and
Impermissible combinations)		 Pass in BIOL2102 or (ECON1280 and any University level 2 course) or (SDST1601 and any University level 2 course) or (SDST1602 and any University level 2 course) or SDST2601 or (SDST1603 and any University level 2 course) or SDST2901; and
Not for students who have passed MATH3901, or have already enrolled in this course.
Only for students admitted in 2025 and thereafter.
Course Status with Related Major/Minor /Professional Core 2U000C00 Course not offered under any Major/Minor/Professional core
2024 Major in Statistics ( Disciplinary Elective )
2024 Minor in Statistics ( Disciplinary Elective )
2023 Major in Statistics ( Disciplinary Elective )
2023 Minor in Statistics ( Disciplinary Elective )
2022 Major in Statistics ( Disciplinary Elective )
2022 Minor in Statistics ( Disciplinary Elective )
2021 Major in Statistics ( Disciplinary Elective )
2021 Minor in Statistics ( Disciplinary Elective )
Course to PLO Mapping 2024 Major in Statistics < PLO 4,5,6 >
2023 Major in Statistics < PLO 4,5,6 >
2022 Major in Statistics < PLO 4,5,6 >
2021 Major in Statistics < PLO 4,5,6 >
Offer in 2025 - 2026 Y        1st sem    Examination No Exam     
Offer in 2026 - 2027 Y
Course Grade A+ to F
Grade Descriptors
A Demonstrate thorough mastery at an advanced level of extensive knowledge and skills required for attaining all the course learning outcomes. Show strong analytical and critical abilities and logical thinking, with evidence of original thought, and ability to apply knowledge to a wide range of complex, familiar and unfamiliar situations. Apply highly effective organizational and presentational skills.
B Demonstrate substantial command of a broad range of knowledge and skills required for attaining at least most of the course learning outcomes. Show evidence of analytical and critical abilities and logical thinking, and ability to apply knowledge to familiar and some unfamiliar situations. Apply effective organizational and presentational skills.
C Demonstrate general but incomplete command of knowledge and skills required for attaining most of the course learning outcomes. Show evidence of some analytical and critical abilities and logical thinking, and ability to apply knowledge to most familiar situations. Apply moderately effective organizational and presentational skills.
D Demonstrate partial but limited command of knowledge and skills required for attaining some of the course learning outcomes. Show evidence of some coherent and logical thinking, but with limited analytical and critical abilities. Show limited ability to apply knowledge to solve problems. Apply limited or barely effective organizational and presentational skills.
Fail Demonstrate little or no evidence of command of knowledge and skills required for attaining the course learning outcomes. Lack of analytical and critical abilities, logical and coherent thinking. Show very little or no ability to apply knowledge to solve problems. Organization and presentational skills are minimally effective or ineffective.
Communication-intensive Course Y
Course Type Lecture-based course
Course Teaching
& Learning Activities
Activities Details No. of Hours
Lectures 36.0
Tutorials 12.0
Reading / Self study 100.0
Assessment Methods
and Weighting
Methods Details Weighting in final
course grade (%)		 Assessment Methods
to CLO Mapping
Assignments 4 assignments 20.0 1,2,3,4
Presentation Final project presentation 20.0 1,2,3,4
Project reports Project proposal + Final project written report 30.0 1,2,3,4
Test Class test 30.0 1,2,3,4
Required/recommended reading
and online materials		 B. Render, R. Stair, M. Hanna: Quantitative Analysis for Management, 10th edition, Pearson
Wayne L. Winston: Operations Research, 4th edition, Thomson Learning
H. Taha: An Introduction to Operations Research, 8th edition, Pearson International Edition
F.S. Hillier and G, J. Lieberman: An Introduction to Operations Research
Robert F.V. Anderson, Holt, Rinehart and Winston: Introduction to Linear Algebra
Course Website http://moodle.hku.hk
Additional Course Information NIL