Open AccessA Combination of Palmer Algorithm and Gupta Algorithm for Scheduling Problem in Apparel Industry
Author(s) -
Cecilia Esti Nugraheni,
Luciana Abednego,
Maria Widyarini,
Luciana Abednego Cecilia E. Nugraheni
Publication year - 2021
Publication title -
international journal of fuzzy logic systems
Language(s) - English
Resource type - Journals
ISSN - 1839-6283
DOI - 10.5121/ijfls.2021.11101
Subject(s) - heuristics , computer science , algorithm , scheduling (production processes) , heuristic , mathematical optimization , genetic algorithm , clothing industry , job shop scheduling , class (philosophy) , clothing , industrial engineering , engineering , mathematics , artificial intelligence , machine learning , schedule , archaeology , history , operating system
The apparel industry is a class of textile industry. Generally, the production scheduling problem in the apparel industry belongs to Flow Shop Scheduling Problems (FSSP). There are many algorithms/techniques/heuristics for solving FSSP. Two of them are the Palmer Algorithm and the Gupta Algorithm. Hyper-heuristic is a class of heuristics that enables to combine of some heuristics to produce a new heuristic. GPHH is a hyper-heuristic that is based on genetic programming that is proposed to solve FSSP [1]. This paper presents the development of a computer program that implements the GPHH. Some experiments have been conducted for measuring the performance of GPHH. From the experimental results, GPHH has shown a better performance than the Palmer Algorithm and Gupta Algorithm.