Computers and Industrial Engineering
A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling
Computers and Operations Research
Flexible job-shop scheduling with parallel variable neighborhood search algorithm
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Non-identical parallel machine scheduling using genetic algorithm
Expert Systems with Applications: An International Journal
A genetic algorithm-based scheduler for multiproduct parallel machine sheet metal job shop
Expert Systems with Applications: An International Journal
An adaptive annealing genetic algorithm for the job-shop planning and scheduling problem
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Based on Genetic Algorithm (GA) and Grouping Genetic Algorithm (GGA), this research develops a scheduling algorithm for job shop scheduling problem with parallel machines and reentrant process. This algorithm consists of two major modules: machine selection module (MSM) and operation scheduling module (OSM). MSM helps an operation to select one of the parallel machines to process it. OSM is then used to arrange the sequences of all operations assigned to each machine. A real weapon production factory is used as a case study to evaluate the performance of the proposed algorithm. Due to the high penalty of late delivery in military orders and high cost of equipment investment, total tardiness, total machine idle time and makespan are important performance measures used in this study. Based on the design of experiments, the parameters setting for GA and GGA are identified. Simulation results demonstrate that MSM and OSM respectively using GGA and GA outperform current methods used in practice.