Decision Making
Code: 44760 ECTS Credits: 9| Degree | Type | Year |
|---|---|---|
| 4318306 Logistics and Supply Chain Management | OB | 1 |
Contact
- Name:
- Juan Jose Ramos Gonzalez
- Email:
- juanjose.ramos@uab.cat
Teachers
- Zhiqiang Liu
- (External) Pau Folch
Teaching groups languages
You can view this information at the end of this document.
Prerequisites
None
Objectives and Contextualisation
Along a supply chain hundreds and thousands of individual decisions have to be made and coordinated every minute. These decisions are of different importance. They comprise the rather simple question "Which job has to be scheduled next on a respective machine?" as well as the very serious task whether to open or close a factory. The more important a decision is, the better it has to be prepared. This preparation is the job of planning in its widest sense. Planning supports decision-making by identifying alternatives of future activities and selecting some good ones or even the best one. Planning can be subdivided into the phases:
- recognition and analysis of a decision problem,
- definition of objectives,
- forecasting of future developments,
- identification and evaluation of feasible activities (solutions), and finally
- selection of good solutions.
Supply chains are very complex. Not every detail that has to be dealt with in reality can and should be respected in a plan and during the planning process. Therefore, it is always necessary to abstract from reality and to use a simplified copy of reality, a so-called model, as a basis for establishing a plan. The "art of model building" is to represent reality as simple as possible but as detailed as necessary, i. e. without ignoring any serious real world constraints.
The main objective of this subject is to introduce quantitative methods and optimization techniques aimed to help the planning activities and, therefore, to support the decision making process. These methods are based in the use of formal models and their corresponding solving techniques. The student will learn how to model the system and its decision making process and then how to apply the methods and techniques to select the optimal solutions. Basic case studies representing typical problems (e.g. planning, scheduling, distribution or routing) are used in the learning process.
Learning Outcomes
- CA04 (Competence) Develop arguments based on optimisation models and quantitative techniques.
- CA05 (Competence) Systematise, document and reflect on problem-solving and decision-making processes in order to identify the lessons that have been learned.
- CA06 (Competence) Gather and formulate the main aspects involved in solving decision-making challenges by deciphering the decision variables and limitations, and proposing a solution.
- KA07 (Knowledge) Identify the principal methods and techniques that support decision making.
- KA08 (Knowledge) Model the system in relation to the decision-making process.
- SA07 (Skill) Analyse, structure and propose mechanisms to identify and solve a decision-making problem with logistics systems.
- SA08 (Skill) Select and apply the appropriate methodologies and strategies to design a solution to a decision-making problem in LCSM.
- SA09 (Skill) Evaluate and compare alternatives in order to find a solution and evaluate hypotheses by combining intuition and analytical methods to identify the best option.
Content
THEORY
DM.T.1: Introduction to Decision Making:
- DM in LSCM:
- SCM modeling
- Advanced Planning
- Quantitative methods
- Planning and scheduling
- Forecasting
DM.T.2: Optimization methods:
- Linear and integer programming
- Constraint programming
- AI methods
DM.T.3: Production planning:
- Types of constraints
- Modeling structures
DM.T.4: Optimization of scheduling problems:
- Job sequencing
- Resource allocation
- Job and resource scheduling
DM.T.5: Heuristics and evolutionary methods:
- Introduction to evolutionary algorithms
- Heuristics in planning problems
DM.T.6: Heuristics and evolutionary methods
- Heuristics in Transport Planning
PROBLEMS
DM.P.1: Examples:
- Demand forecasting
- Production mix
DM.P.2: MILP modeling exercises
DM.P.3: Production planning models
DM.P.4: Production scheduling models
DM.P.5: Distribution: warehouses & inventory
DM.P.6: Transport network models
PRACTISE
DM.L.1: Introduction to OPL:
- S/W installation
- IDE overview
DM.L.2: OPL:
- MILP programming
- CP programming
DM.L.3: Productionplanning
DM.L.4: Production planning
DM.L.5: Heuristics and evolutionary methods
- Introduction to HeuristicLab
- Solving Job Shop Scheduling Problem in HeuristicLab
DM.L.6: Solving Transport and VRP problems
SEMINARS
Management Information Systems in Business: Role of IT in modern business
Activities and Methodology
| Title | Hours | ECTS | Learning Outcomes |
|---|---|---|---|
| Type: Directed | |||
| Problem sessions | 8.5 | 0.34 | |
| Seminars | 10 | 0.4 | |
| Theory lectures | 31.5 | 1.26 | |
| Type: Supervised | |||
| Practise sessions | 18 | 0.72 | |
| Type: Autonomous | |||
| Personal study | 50 | 2 | |
| Problem solving and report writing | 107 | 4.28 |
The course is organized by means of traditional lectures combined with seminars. The learning process will combine the following activities:
- Theory lectures
- Problem sessions
- Practise sessions: computer lab
- Teamwork and oral presentation
- Autonomous work
Practical case studies and optimization tools are used for promoting students hand on skills.
The proposed teaching methodology may undergo some modifications according to the restrictions imposed by the health authorities on on-campus courses.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Assessment
Continous Assessment Activities
| Title | Weighting | Hours | ECTS | Learning Outcomes |
|---|---|---|---|---|
| B1-Introduction to IT project | 10% | 0 | 0 | KA07, SA09 |
| B2-Planning & Scheduling practical cases | 70% | 0 | 0 | CA04, CA05, CA06, KA07, KA08, SA07, SA08, SA09 |
| B3-Heuristics practical cases | 20% | 0 | 0 | KA07, KA08, SA09 |
a) Scheduled evaluation process and activities
The subject does not have written exams. The evaluation is based on the different works presented during the semester.
The submission deadlines for the different reports will be published in the moodle classroom of the virtual campus since the very beginning of the semester. Deadlines are subject to possible reschedules in case of unforeseen events. The Virtual Campus is the only channel to communicate the most updated schedule, since it is assumed that this is the only platform for exchanging this sort of information between faculty and students.
b) Programming evaluation activities
The schedule of the regular evaluation activities will be published on the virtual campus at the early beginning fo the semester. Dates for retaking process will be published at the examination section of the School of Engineering website.
c) Retaking process
In accordance with the Academic Regulations of the UAB, participating in retaking process requires the student to have been previously evaluated in the set of evaluation activities, the weight of which is equivalent to a minimum of two thirds of the total grade of the subject or module.
Practice work can't be retaken and must be submitted within the specified deadlines.
An Assay course work failed in the first instance can be recovered on the examination date set by the programme coordination. Re-taking will consist in the presentation of the corrected work according to the indications received by the professor. In this case, as long as the work meets the MINIMUM requirements, the work will be graded with a 5.
d) Procedure to review qualifications
For each evaluation activity, a place, date and time in which the student can review the activity with the teacher will be indicated. The faculty responsible for the subject will assess the presented complaints regarding the awarded grade. The student can complain in the given date, but the activity will not be reviewed later.
e) Qualifications
The final grade will be calculated from the assessment of the following evaluation activities:
B1: Small project report related to the introduction to IT seminars (10%).
B2: Combines an Assay (50%) or small project (team work) and the solution reports (20%) of four practical exercises (individual work) in the field of Planning & Scheduling, where MILP and CP optimization methods are used to solve the problems.
B3: Solution reports of two cases where heuristics methods are used to solve the problem (20%).
In order to average all the evaluation activities, the mark of each of them must be above 4 points (out of 10). All the report-based activities must be submitted within the due dates specified by the professor. If a report-based activity is failed, the student will be asked to re-submit its report according to the corrections/indications provided by the professor.
If any of the components of the evaluation has a value lower than 4, the qualification will be Fail
The Assay qualification (belong to B2) has two components:
- Overall evaluation of the work (90% of the mark). Both the report and the developed project will be evaluated.
- Oral defense (10% of the mark): Teacher's assessment during the oral presentation.
Granting a distinction grade is the decision of the subject faculty. The regulations ofthe UAB indicate that distinctions may be awarded to students who have obtained a final grade equalor greater than 9.00. Distinction awards cannot exceed 5% of enrolled students.
The rating of "Assesment not possible" (Not Submitted) will be obtained only if no evaluation activity is delivered.
f) Irregularities by the student, copy and plagiarism
Without prejudice to other disciplinary measures deemed appropriate, and in accordance with current academic regulations, any irregularity committed by the student, which could lead to an alteration of the evaluation act, will be scored with a zero. Therefore, copying or allowing to copy a practice or any other activity spoiling the evaluation will imply failing with a zero, and if the activity is required to pass the subject, the whole course will be failed. The evaluation activities qualified in this way and by this procedure will not be recoverable, and therefore the subject will be failed directly without the opportunity to retaking it in the same academic year.
g) Evaluation of students retaking the whole subject
Those students retaking the whole subject must follow the same evaluation activities as for the first time.
Bibliography
Hartmurt Stadlert and Cristoph Kilger (Eds.) Supply Chain Management and Advanced Planning. Third Edition. Springer, 2005. (Electronic version available at the university library)
Ioannis T. Christou. Quantitative Methods in Supply Chain Management. Models and Algorithms. Springer, 2012. (Electronic version available at the university library)
H. Paul Williams. Model Building in Mathematical Programming. Wiley. 2013 (5th edition) Further readings
Joseph Geunes, Panos M. Pardalos and H. Edwin Romeijn (Eds.) Supply Chain Management: Models, Applications, and Research Directions. Kluwer Academic Publishers, 2002. (Electronic version available at the university library)
F. Robert Jacobs, William L. Berry, D. Clay Waybark and Thomas E. Vollmann. Manufacturing Planning and Control for Supply Chain Management. McGraw-Hill, 2011 (6th edition)
F. Robert Jacobs and Richard B. Chase. Operations and Supply Chain management. McGraw-Hill Irwing, 2011 (13 th edition)
Other relevant literature can be provided during the lecturing period.
Software
During the course we will use the IBM ILOG optimization platform that you can install on your computers.
How to get the ILOG Student Edition platform (When starting the course):
https://www.ibm.com/products/ilog-cplex-optimization-studio?mhsrc=ibmsearch_a&mhq=ilog
Register on the platform with your email address @ e-campus.uab.cat
Language list
| Name | Group | Language | Semester | Turn |
|---|---|---|---|---|
| (PAULm) Classroom practices (master) | 10 | English | first semester | morning-mixed |
| (PLABm) Practical laboratories (master) | 10 | English | first semester | morning-mixed |
| (TEm) Theory (master) | 10 | English | first semester | morning-mixed |