The Storage Location Assignment Problem An optimized simulated annealing algorithm - solving the storage location assignment problem with correlated batched orders
(2023) In Bachelor's Theses in Mathematical Sciences NUMK11 20221Mathematics (Faculty of Sciences)
Centre for Mathematical Sciences
- Abstract
- The main topic of this thesis is the storage location assignment problem, which can also be seen as a traveling salesman problem. The objective is to find the shortest path between items to be picked at a medium-sized warehouse. Orders come in batches consisting of items that will be assembled in-house. Therefore, it is essential to pick up all the items
contained in the batch before they are dropped off at the assembly line of the warehouse. To solve this problem, we constructed mathematical models consisting of the warehouse layout and a cost function to minimize. The mathematical models are applied to a real- world scenario. Therefore, we had to consider the warehouse’s physical layout. It included being able to store items at four... (More) - The main topic of this thesis is the storage location assignment problem, which can also be seen as a traveling salesman problem. The objective is to find the shortest path between items to be picked at a medium-sized warehouse. Orders come in batches consisting of items that will be assembled in-house. Therefore, it is essential to pick up all the items
contained in the batch before they are dropped off at the assembly line of the warehouse. To solve this problem, we constructed mathematical models consisting of the warehouse layout and a cost function to minimize. The mathematical models are applied to a real- world scenario. Therefore, we had to consider the warehouse’s physical layout. It included being able to store items at four different levels. Moreover, there were restrictions at
specific aisles, such as a pillar in the middle of an aisle. The cost function was minimized by using an algorithm known as the simulated annealing algorithm. The algorithm is explained through a mathematical process known as Markov chains. Parameters used in the model are adjusted to see how it affects the results and computational time. It is of great importance to mention that solutions are only close to an optimal one since the nature of the problem is unsolvable in polynomial time. The storage location solution presented in this thesis significantly reduces the pick and travel times compared to the warehouse’s initial layout. Moreover, optimization techniques in Python are investigated and implemented, and the impact of the computational time is measured and presented. (Less) - Popular Abstract
- Have you ever wondered what happens behind the scenes when you order a product online? One of the ongoing challenges in the e-commerce industry is the storage location assignment problem. This mathematical problem, also known as the traveling salesman problem, seeks to find the most efficient path to pick up items in a warehouse. In this thesis, we tackle this problem in a medium-sized warehouse, which presents additional challenges due to its multiple storage levels and restricted aisles. To solve this problem, we developed a mathematical model that uses the simulated annealing algorithm, a technique inspired by the cooling process of metals. By optimizing the storage locations using this algorithm, we achieved significant reductions in... (More)
- Have you ever wondered what happens behind the scenes when you order a product online? One of the ongoing challenges in the e-commerce industry is the storage location assignment problem. This mathematical problem, also known as the traveling salesman problem, seeks to find the most efficient path to pick up items in a warehouse. In this thesis, we tackle this problem in a medium-sized warehouse, which presents additional challenges due to its multiple storage levels and restricted aisles. To solve this problem, we developed a mathematical model that uses the simulated annealing algorithm, a technique inspired by the cooling process of metals. By optimizing the storage locations using this algorithm, we achieved significant reductions in pick and travel times compared to the initial layout of the warehouse. Additionally, we explored optimization strategies in Python and discovered libraries that can reduce computational time for this algorithm. Our approach offers practical solutions for real-world scenarios and sheds light on the mathematical challenges that warehouse operations face daily. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9112895
- author
- Green, Pontus LU
- supervisor
- organization
- course
- NUMK11 20221
- year
- 2023
- type
- M2 - Bachelor Degree
- subject
- keywords
- Storage location assignment problem, Traveling salesman problem, mathematical modelling, Simulated annealing algorithm, E-commerce, Warehouse optimization, Python optimization techniques
- publication/series
- Bachelor's Theses in Mathematical Sciences
- report number
- LUNFNA-4044-2023
- ISSN
- 1654-6229
- other publication id
- 2023:K8
- language
- English
- id
- 9112895
- date added to LUP
- 2023-05-04 13:25:15
- date last changed
- 2023-05-04 13:25:15
@misc{9112895,
abstract = {{The main topic of this thesis is the storage location assignment problem, which can also be seen as a traveling salesman problem. The objective is to find the shortest path between items to be picked at a medium-sized warehouse. Orders come in batches consisting of items that will be assembled in-house. Therefore, it is essential to pick up all the items
contained in the batch before they are dropped off at the assembly line of the warehouse. To solve this problem, we constructed mathematical models consisting of the warehouse layout and a cost function to minimize. The mathematical models are applied to a real- world scenario. Therefore, we had to consider the warehouse’s physical layout. It included being able to store items at four different levels. Moreover, there were restrictions at
specific aisles, such as a pillar in the middle of an aisle. The cost function was minimized by using an algorithm known as the simulated annealing algorithm. The algorithm is explained through a mathematical process known as Markov chains. Parameters used in the model are adjusted to see how it affects the results and computational time. It is of great importance to mention that solutions are only close to an optimal one since the nature of the problem is unsolvable in polynomial time. The storage location solution presented in this thesis significantly reduces the pick and travel times compared to the warehouse’s initial layout. Moreover, optimization techniques in Python are investigated and implemented, and the impact of the computational time is measured and presented.}},
author = {{Green, Pontus}},
issn = {{1654-6229}},
language = {{eng}},
note = {{Student Paper}},
series = {{Bachelor's Theses in Mathematical Sciences}},
title = {{The Storage Location Assignment Problem An optimized simulated annealing algorithm - solving the storage location assignment problem with correlated batched orders}},
year = {{2023}},
}