Tabu search method for solving multiobjective job shop scheduling problem

Scheduling is widely studied and it involves of complex combinatorial optimization problems. A job shop scheduling problem (JSSP) is one of the common scheduling problems. The application of it ranges from manufacturing to services industries. It can be considered as a NP-hard problem. A lot of rese...

Full description

Bibliographic Details
Main Author: Awang, Nor Fauzana (Author)
Format: Thesis
Published: 2015-01.
Subjects:
Online Access:Get fulltext
LEADER 01550 am a22001573u 4500
001 53981
042 |a dc 
100 1 0 |a Awang, Nor Fauzana  |e author 
245 0 0 |a Tabu search method for solving multiobjective job shop scheduling problem 
260 |c 2015-01. 
520 |a Scheduling is widely studied and it involves of complex combinatorial optimization problems. A job shop scheduling problem (JSSP) is one of the common scheduling problems. The application of it ranges from manufacturing to services industries. It can be considered as a NP-hard problem. A lot of research has been performed in this particular area to obtain an effective schedule jobs for various objectives. More than one objective in a single problem is considered multiobjective problem. Two objectives, which are the maximum completion time (makespan) and total weighted tardiness, are measured simultaneously to improve the performance of the schedule. In this study, metaheuristic method known as tabu search algorithm is proposed to tackle the problem. But, first of all Giffler and Thompson (GT) algorithm will be applied to obtain the potential initial solution for the respective problem. Benchmark problem is used to evaluate and study the performance of the proposed algorithm. Results shows that tabu search provide a better solution compared to simulated annealing method. 
546 |a en 
650 0 4 |a QA Mathematics 
655 7 |a Thesis 
787 0 |n http://eprints.utm.my/id/eprint/53981/ 
856 |z Get fulltext  |u http://eprints.utm.my/id/eprint/53981/25/NorFauzanaAwangMFS2015.pdf