Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

Muhammad Kamal Amjad*, Shahid Ikramullah Butt, Rubeena Kousar, Riaz Ahmad, Mujtaba Hassan Agha, Zhang Faping, Naveed Anjum, Umer Asgher

*此作品的通讯作者

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115 引用 (Scopus)

摘要

Flexible Job Shop Scheduling Problem (FJSSP) is an extension of the classical Job Shop Scheduling Problem (JSSP). The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA) have gained the most popularity. Keeping in view this aspect, this article presents a comprehensive literature review of the FJSSPs solved using the GA. The survey is further extended by the inclusion of the hybrid GA (hGA) techniques used in the solution of the problem. This review will give readers an insight into use of certain parameters in their future research along with future research directions.

源语言英语
文章编号9270802
期刊Mathematical Problems in Engineering
2018
DOI
出版状态已出版 - 2018

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