Please use this identifier to cite or link to this item:
Kumar, Vijay M.
Murthy, ANN
Chandrashekara, K.
Year of Publication: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Publisher:] SpringerOpen [Place:] Heidelberg [Volume:] 8 [Year:] 2012 [Pages:] 1-10
The production planning problem of flexible manufacturing system (FMS) concerns with decisions that have to be made before an FMS begins to produce parts according to a given production plan during an upcoming planning horizon. The main aspect of production planning deals with machine loading problem in which selection of a subset of jobs to be manufactured and assignment of their operations to the relevant machines are made. Such problems are not only combinatorial optimization problems, but also happen to be non-deterministic polynomial-time-hard, making it difficult to obtain satisfactory solutions using traditional optimization techniques. In this paper, an attempt has been made to address the machine loading problem with objectives of minimization of system unbalance and maximization of throughput simultaneously while satisfying the system constraints related to available machining time and tool slot designing and using a meta-hybrid heuristic technique based on genetic algorithm and particle swarm optimization. The results reported in this paper demonstrate the model efficiency and examine the performance of the system with respect to measures such as throughput and system utilization.
flexible manufacturing system
production planning
hybrid algorithm optimization
Persistent Identifier of the first edition: 
Creative Commons License:
Document Type: 

Files in This Item:
571.64 kB

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.