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


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


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.


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