학술논문

A Genetic Algorithm to Minimize the Total Tardiness for M-Machine Permutation Flowshop Problems
Document Type
article
Source
Journal of Entrepreneurship, Management and Innovation, Vol 8, Iss 2, Pp 26-43 (2012)
Subject
genetic algorithm
scheduling
permutation flowshop
tardiness
Management. Industrial management
HD28-70
Business
HF5001-6182
Language
English
ISSN
2299-7326
Abstract
The m-machine, n-job, permutation flowshop problem with the total tardiness objective is a common scheduling problem, known to be NP-hard. Branch and bound, the usual approach to finding an optimal solution, experiences difficulty when n exceeds 20. Here, we develop a genetic algorithm, GA, which can handle problems with larger n. We also undertake a numerical study comparing GA with an optimal branch and bound algorithm, and various heuristic algorithms including the well known NEH algorithm and a local search heuristic LH. Extensive computational experiments indicate that LH is an effective heuristic and GA can produce noticeable improvements over LH.