Paper Info
Title
A New Meta-Heuristic Algorithm for Solving the Flexible Dynamic Job-Shop Problem with Parallel Machines.
Abstract
In a real manufacturing environment, the set of tasks that should be scheduled is changing over the time, which means that scheduling problems are dynamic. Also, in order to adapt the manufacturing systems with fluctuations, such as machine failure and create bottleneck machines, various flexibilities are considered in this system. For the first time, in this research, we consider the operational flexibility and flexibility due to Parallel Machines (PM) with non-uniform speed in Dynamic Job Shop (DJS) and in the field of Flexible Dynamic Job-Shop with Parallel Machines (FDJSPM) model. After modeling the problem, an algorithm based on the principles of Genetic Algorithm (GA) with dynamic two-dimensional chromosomes is proposed. The results of proposed algorithm and comparison with meta-heuristic data in the literature indicate the improvement of solutions by 1.34 percent for different dimensions of the problem.
Year
DOI
Venue
2019
10.3390/sym11020165
SYMMETRY-BASEL
Keywords
Field
DocType
Dynamic job-shop,Parallel Machines,Maximum flow-time of components,Genetic Algorithm
Bottleneck,Manufacturing systems,Scheduling (computing),Meta heuristic,Job shop,Algorithm,Machine failure,Mathematics,Genetic algorithm
Journal
Volume
Issue
Citations 
11
2
0
PageRank 
References 
Authors
0.34
23
6
Name
Order
Citations
PageRank
Arun Kumar11427132.32
Mohsen Yaghoubi Suraki241.45
Mehdi Sadeghilalimi300.34
Seyed Mostafa Bozorgi4192.36
ali asghar rahmani hosseinabadi5737.54
jin wang624336.79