Job Shop Scheduling Problem with Job Sizes and Inventories

Autor: Shen Xinyi, Ge Yan, Wang Aimin, Ye Jieran
Rok vydání: 2020
Předmět:
Zdroj: 2020 IEEE 11th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT).
Popis: In order to satisfy better the actual situation of modern manufacturing enterprise workshop scheduling and the need of lean production, this paper considers the job shop scheduling problem with inventories and batch size of each job. In this problem, for some jobs, if the inventory can meet the demand, no further processing is required. Therefore, the actual processing batch size of a job is its demand size minus the inventory size of the job. Job sizes influence the starting time of operations. With the objective of minimizing the makespan of all jobs, a mixed integer programming model is established. A genetic algorithm is used to solve the proposed model. Finally, a program was developed with the actual data, job sizes, inventories and the job sizes of starting operations to verify the feasibility and effectiveness of the algorithm. The result shows that the algorithm achieves satisfactory results in all indexes mentioned above.
Databáze: OpenAIRE