Program Overview

Program Overview

The Decision-Making for Low Carbon Management program is designed to equip students with the skills and knowledge necessary to make informed decisions in the field of low carbon management. The program focuses on the application of mathematical programming to analyze and solve problems related to low carbon management.

Course Description

Implementing and deepening low carbon-oriented management is essential for the world today to respond to climate change effectively and to realize the transition to sustainable development. Analytical tools that aid the decision-making of shifting to low carbon would be thus desirable. In the arena of evaluating the effects of technology and innovation, the focus of the research has seen a swift shift from emphasizing on economic returns alone to being more inclusive, taking into consideration the dimensions of society, environment, policy, and etc. Conventional quantitative methods such as statistical analysis, appraisal by index, and econometrics are limited in that they cannot capture the interplay between the many socioeconomic, resources, and environmental factors. Mathematical programming can provide analytical tools with an integrated perspective however.

Course Objectives

The course aims to introduce the basic principles of linear programming to students and to train the skills of programming with GAMS (General Algebraic Modeling System). Students shall learn to formulate mathematical models in the area of low carbon management, implement the models and conduct scenario analysis using GAMS, and interpret the results.

Course Schedule

The course is divided into 16 weeks, with the following topics covered:

• Week #1: Low carbon management & applied mathematical programming (a)
• Week #2: Low carbon management & applied mathematical programming (b) T2. Matrix solution, interpretation, duality, and sensitivity (a)
• Week #3: T2. Matrix solution, interpretation, duality, and sensitivity (b)
• Week #4: L1. Introduction to GAMS, Formulating a general problem
• Week #5: T3. Typical low carbon management problems & linear programming model formulation
• Week #6: T4. Fixing linear programming models
• Week #7: L2. Inspecting a model & reading error messages
• Week #8: L3. Power of GAMS, Good modeling practices, Conditionals (a)
• Week #9: L3. Power of GAMS, Good modeling practices, Conditionals (b) T5. Multi-objective programming model and its use in low carbon management (a)
• Week #10: T5. Multi-objective programming model and its use in low carbon management (b)
• Week #11: T6. Nonlinear quadratic programming model and modeling of low carbon economy (a)
• Week #12: T6. Nonlinear quadratic programming model and modeling of low carbon economy (b) L4. GAMS Check, Examining a model for flaws (a)
• Week #13: L4. GAMS Check, Examining a model for flaws (b)
• Week #14: T7. Risk programming, stochastic programming, and uncertainty for low carbon management
• Week #15: L5. Report writing L6. Conducting comparative analysis
• Week #16: T8. Integer programming and low carbon investment

Grading Policy

The grading policy for the course is as follows:

• Attendance: 10%
• Homework (Theory): 30%
• Homework (Programming): 20%
• Final Exam: 40%

Textbooks and References

The course uses the following textbooks and references:

• McCarl, B.A. & Spreen, T.H., Applied Mathematical Programming Using Algebraic Systems
• McCarl, B.A., AGEC 641 -- Applied Mathematical Programming

Prerequisites

The prerequisite for the course is Linear Algebra.

Credits and Teaching Hours

The course is worth 2 credits and has 32 teaching hours.

Language of Instruction

The language of instruction for the course is English.

School and Department

The course is offered by the China-UK Low Carbon College.