Javascript must be enabled for the correct page display

Job Shop Scheduling with Metaheuristics

Haan, H. de (2016) Job Shop Scheduling with Metaheuristics. Master's Thesis / Essay, Artificial Intelligence.

[img]
Preview
Text
Job_Shop_Scheduling_with_Metah_1.pdf - Published Version

Download (983kB) | Preview
[img] Text
Toestemming.pdf - Other
Restricted to Backend only

Download (488kB)

Abstract

For this thesis, different algorithms were created to solve the problem of Jop Shop Scheduling with a number of constraints. More specifically, the setting of a (simplified) car workshop was used: the algorithms had to assign all tasks of one day to the mechanics, taking into account minimum and maximum finish times of tasks and mechanics, the use of bridges, skill levels and qualifications and the delivery and usage of car parts. The algorithms used in this research are Hill Climbing, a Genetic Algorithm with and without a Hill Climbing component, two different Particle Swarm Optimizers with and without Hill Climbing, Max-Min Ant System with and without Hill Climbing and Tabu Search. Two experiments were performed: one focussed on the speed of the algorithms, the other on their performance. The experiments point towards the Genetic Algorithm with Hill Climbing as the best algorithm for this problem.

Item Type: Thesis (Master's Thesis / Essay)
Degree programme: Artificial Intelligence
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 08:24
Last Modified: 15 Feb 2018 08:24
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/14359

Actions (login required)

View Item View Item