CHAOTIC SIMULATED ANNEALING FOR SOLVING STOCHASTIC DYNAMIC FACILITY LAYOUT PROBLEM

2014 ◽  
Vol 14 (2) ◽  
pp. 67-74 ◽  
Author(s):  
Akash Tayal ◽  
S. Singh
2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Yunfang Peng ◽  
Tian Zeng ◽  
Lingzhi Fan ◽  
Yajuan Han ◽  
Beixin Xia

This paper deals with stochastic dynamic facility layout problem under demand uncertainty in terms of material flow between facilities. A robust approach suggests a robust layout in each period as the most frequent one falling within a prespecified percentage of the optimal solution for multiple scenarios. Mont Carlo simulation method is used to randomly generate different scenarios. A mathematical model is established to describe the dynamic facility layout problem with the consideration of transport device assignment. As a solution procedure for the proposed model, an improved adaptive genetic algorithm with population initialization strategy is developed to reduce the search space and improve the solving efficiency. Different sized instances are compared with Particle Swarm Optimization (PSO) algorithm to verify the effectiveness of the proposed genetic algorithm. The experiments calculating the cost deviation ratio under different fluctuation level show the good performance of the robust layout compared to the expected layout.


2016 ◽  
Vol 253 (1) ◽  
pp. 621-655 ◽  
Author(s):  
Akash Tayal ◽  
Angappa Gunasekaran ◽  
Surya Prakash Singh ◽  
Rameshwar Dubey ◽  
Thanos Papadopoulos

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