LOG904-165 Models in Dynamic Lot Sizing (Autumn 2020)

ECTS Credits:
2.5
Responsible faculty:
Avdeling for logistikk
Campus:
Molde
Course Leader:
Erik Langelo
Teaching language:
English
Study level:
{code=HN, name=Second degree level}
Duration:
½ year

Table of contents

Contents

This seminar gives an overview of dynamic lot size models used in production management. The beginning of the seminar will focus on the seminal model of Wagner and Whitin. Subsequent parts discuss capacitated models and models with pricing, including the aspect of pricing with respect to new technology.

Topics covered: Uncapacitated lot sizing with different formulations. The Wagner-Whitin algorithm and heuristics. Lot sizing with pricing; uncapacitated and capacitated. Various extensions of these models. All models are discrete-time and finite-horizon.

The course is connected to the following study programs

Recommended knowledge

Knowledge of AMPL, some familiarity with mathematical models and algorithms in general.

The student's learning outcomes after passing the exam

After the seminar, students will be able to link practical problems to their corresponding lot size model and find solutions to these problems, using either a commercial solver or a specialized algorithm. Students will be able to describe the differences and similarities between the various models, program the models in AMPL and interpret solutions.

Forms of teaching and learning

Monday-Thursday: lectures at 9:15-12:00, computer lab at 13:15-16:00. Friday: Oral exams based on the assignment.

Exam

Form of assessment: Home assessment without presentation

  • Proportion: 60%
  • Duration: -
  • Grouping: Group
  • Grading scale: Letter (A - F)
  • Support material: All printed and written supporting material

Form of assessment: Oral exam

  • Proportion: 40%
  • Duration: -
  • Grouping:
  • Grading scale: Letter (A - F)
  • Support material: All printed and written supporting material

Pensum

TBA
Last updated from FS (Felles studentsystem) Oct. 14, 2026 4:34:36 AM