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Solving the Storage Location Assignment Problem in the Manufacturing Industry - A Study in Mathematical Modeling & Applied Optimization

Utjés, Kevin LU and Sjöholm, Louise LU (2018) In Master's Theses in Mathematical Sciences FMNM01 20181
Mathematics (Faculty of Engineering)
Abstract
Companies in the manufacturing industry are constantly seeking to be more effective in cutting costs and increase revenue to improve profits. Order picking is often the most expensive operation in the inventory, as it stands for 55% of the inventory operating expenses. Alfa Laval, a heavy industry company, is rolling out a new corporate strategy involving its operations, which this thesis is a part of.

The authors of this thesis developed a tool to support Alfa Laval’s manually operated inventory. The tool was built with a mathematical modeling approach in the programming language Python. It was later tested in real-life settings where it successfully reduced the travel time of picking items in the inventory. The objective was to... (More)
Companies in the manufacturing industry are constantly seeking to be more effective in cutting costs and increase revenue to improve profits. Order picking is often the most expensive operation in the inventory, as it stands for 55% of the inventory operating expenses. Alfa Laval, a heavy industry company, is rolling out a new corporate strategy involving its operations, which this thesis is a part of.

The authors of this thesis developed a tool to support Alfa Laval’s manually operated inventory. The tool was built with a mathematical modeling approach in the programming language Python. It was later tested in real-life settings where it successfully reduced the travel time of picking items in the inventory. The objective was to optimize the storage location of items in the inventory, which was done by introducing heuristic- and metaheuristic algorithms and applying them to a linear- and a quadratic model, known as GAP and QAP. The thesis was written by authors from different majors, creating an interdisciplinary team where both applied their academic backgrounds to achieve the purpose of the thesis. This master thesis is a study in mathematical modeling. (Less)
Please use this url to cite or link to this publication:
author
Utjés, Kevin LU and Sjöholm, Louise LU
supervisor
organization
course
FMNM01 20181
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Mathematical Modeling, Inventory Optimization, Integer Programming, Generalized Assignment Problem, Quadratic Assignment Problem, Heuristic Algorithms, Metaheuristic Algorithms
publication/series
Master's Theses in Mathematical Sciences
report number
LUTFNA-3044-2018
ISSN
1404-6342
other publication id
2018:E28
language
English
id
8945864
date added to LUP
2018-06-11 15:39:21
date last changed
2018-06-11 15:39:21
@misc{8945864,
  abstract     = {Companies in the manufacturing industry are constantly seeking to be more effective in cutting costs and increase revenue to improve profits. Order picking is often the most expensive operation in the inventory, as it stands for 55% of the inventory operating expenses. Alfa Laval, a heavy industry company, is rolling out a new corporate strategy involving its operations, which this thesis is a part of.

The authors of this thesis developed a tool to support Alfa Laval’s manually operated inventory. The tool was built with a mathematical modeling approach in the programming language Python. It was later tested in real-life settings where it successfully reduced the travel time of picking items in the inventory. The objective was to optimize the storage location of items in the inventory, which was done by introducing heuristic- and metaheuristic algorithms and applying them to a linear- and a quadratic model, known as GAP and QAP. The thesis was written by authors from different majors, creating an interdisciplinary team where both applied their academic backgrounds to achieve the purpose of the thesis. This master thesis is a study in mathematical modeling.},
  author       = {Utjés, Kevin and Sjöholm, Louise},
  issn         = {1404-6342},
  keyword      = {Mathematical Modeling,Inventory Optimization,Integer Programming,Generalized Assignment Problem,Quadratic Assignment Problem,Heuristic Algorithms,Metaheuristic Algorithms},
  language     = {eng},
  note         = {Student Paper},
  series       = {Master's Theses in Mathematical Sciences},
  title        = {Solving the Storage Location Assignment Problem in the Manufacturing Industry - A Study in Mathematical Modeling & Applied Optimization},
  year         = {2018},
}