Heuristic driven genetic algorithm for job-shop scheduling

In this project, a local search algorithm has been implemented on a job-shop scheduling program[l] given at the initial stage of the project. The program was tested on 35 JSS benchmarks. The results show a range of performance that is 10% to 15% from the known optimum. Besides proposing and implemen...

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Bibliographic Details
Main Author: Chang, Sau Leng.
Other Authors: Lim Meng Hiot
Format: Theses and Dissertations
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10356/42789
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Institution: Nanyang Technological University
Language: English
Description
Summary:In this project, a local search algorithm has been implemented on a job-shop scheduling program[l] given at the initial stage of the project. The program was tested on 35 JSS benchmarks. The results show a range of performance that is 10% to 15% from the known optimum. Besides proposing and implementing the local search algorithm, the original JSS program is also ported to run on Win32 platforms(Win95 and NT). Its memory handling functions are modified to dynamically handle job-shop problems of any sizes from 5x5 up to 30x30. A Windows based graphical user interface(GUI) is written so that the user is able to modify benchmark specific parameters on the GUI and run several benchmarks in batch mode.