A Combination of Palmer Algorithm and Gupta Algorithm for Scheduling Problem in Apparel Industry


Authors

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

Abstract

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.

Keywords

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