A Genetic Programming based Hyper-Heuristic for Production Scheduling in Apparel Industry


Cecilia E. Nugraheni, Luciana Abednego and Maria Widyarini, Parahyangan Catholic University, Indonesia


The apparel industry is a type of textile industry. One of scheduling problems found in the apparel industry production can be classified as Flow Shop Scheduling Problems (FSSP). GPHH for FSSP is a genetic programming based hyper-heuristic techniques to solve FSSP[1]. The algorithm basically aims to generate new heuristics from two basic (low-level) heuristics, namely Palmer Algorithm and Gupta Algorithm. This paper describes the implementation of the GPHH algorithm and the results of experiments conducted to determine the performance of the proposed algorithm. The experimental results show that the proposed algorithm is promising, has better performance than Palmer Algorithm and Gupta Algorithm.


Hyper-heuristic, Genetic Programming, Palmer Algorithm, Gupta Algorithm, Flow Shop Scheduling Problem, Apparel Industry.

Full Text  Volume 10, Number 12