کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
566518 | 875991 | 2009 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: A hybrid heuristic to solve the parallel machines job-shop scheduling problem A hybrid heuristic to solve the parallel machines job-shop scheduling problem](/preview/png/566518.png)
This paper presents an advanced software system for solving the flexible manufacturing systems (FMS) scheduling in a job-shop environment with routing flexibility, where the assignment of operations to identical parallel machines has to be managed, in addition to the traditional sequencing problem. Two of the most promising heuristics from nature for a wide class of combinatorial optimization problems, genetic algorithms (GA) and ant colony optimization (ACO), share data structures and co-evolve in parallel in order to improve the performance of the constituent algorithms. A modular approach is also adopted in order to obtain an easy scalable parallel evolutionary-ant colony framework. The performance of the proposed framework on properly designed benchmark problems is compared with effective GA and ACO approaches taken as algorithm components.
Journal: Advances in Engineering Software - Volume 40, Issue 2, February 2009, Pages 118–127