کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5127429 1489053 2017 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A NSGA-II based memetic algorithm for multiobjective parallel flowshop scheduling problem
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
A NSGA-II based memetic algorithm for multiobjective parallel flowshop scheduling problem
چکیده انگلیسی


- Investigate a parallel non-identical flowshop scheduling problem.
- Develop a multiobjecitve model considering efficiency and cost criteria.
- Propose a novel NSGA-II based memetic algorithm to solve the model.
- Proposed algorithm outperforms two popular multiobjective EAs significantly.

In many real-world manufacturing applications, a number of parallel flowshops are often used to process the jobs. The scheduling problem in this parallel flowshop system has gained an increasing concern from the operational research community; however, multiple scheduling criteria are rarely considered simultaneously in the literature. In this paper, a special parallel flowshop scheduling (PFSS) problem that consists of two parallel non-identical shops, one with two consecutive machines and the other with only one machine, is investigated with two objective functions of minimizing the total flow time of jobs and the number of tardy jobs in the two-machine flowshop. A multiobjective evolutionary algorithm (MOEA) based memetic algorithm hybridizing the local search technique into the framework of NSGA-II, which is well known as the most popular MOEA, is proposed for addressing the investigated PFSS problem. A set of test instances are employed to examine the performance of the proposed algorithm in comparison with two peer MOEAs, which also adopt the similar algorithm mechanism of NSGA-II. Experimental results indicate the effectiveness and efficiency of the proposed NSGA-II based memetic algorithm in solving the multiobjective PFSS problem.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 113, November 2017, Pages 185-194
نویسندگان
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