Bandits Help Simulated Annealing to Complete a Maximin Latin Hypercube Design

2018 ◽  
pp. 280-288
Author(s):  
Christian Hamelain ◽  
Kaourintin Le Guiban ◽  
Arpad Rimmel ◽  
Joanna Tomasik
Keyword(s):  
Simulated Annealing ◽  
Latin Hypercube Design ◽  
Latin Hypercube

scholarly journals Adaptive Response Surface Method Using Inherited Latin Hypercube Design Points

2003 ◽  
Vol 125 (2) ◽  
pp. 210-220 ◽  
Author(s):  
G. Gary Wang
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Adaptive Response ◽  
High Dimensional ◽  
Latin Hypercube Design ◽  
Latin Hypercube ◽  
Design Problems ◽  
Surface Method ◽  
Adaptive Response Surface Method ◽  
Design Experiments

This paper addresses the difficulty of the previously developed Adaptive Response Surface Method (ARSM) for high-dimensional design problems. ARSM was developed to search for the global design optimum for computation-intensive design problems. This method utilizes Central Composite Design (CCD), which results in an exponentially increasing number of required design experiments. In addition, ARSM generates a complete new set of CCD points in a gradually reduced design space. These two factors greatly undermine the efficiency of ARSM. In this work, Latin Hypercube Design (LHD) is utilized to generate saturated design experiments. Because of the use of LHD, historical design experiments can be inherited in later iterations. As a result, ARSM only requires a limited number of design experiments even for high-dimensional design problems. The improved ARSM is tested using a group of standard test problems and then applied to an engineering design problem. In both testing and design application, significant improvement in the efficiency of ARSM is realized. The improved ARSM demonstrates strong potential to be a practical global optimization tool for computation-intensive design problems. Inheriting LHD points, as a general sampling strategy, can be integrated into other approximation-based design optimization methodologies.

A novel algorithm of maximin Latin hypercube design using successive local enumeration

2012 ◽  
Vol 44 (5) ◽  
pp. 551-564 ◽  
Author(s):  
Huaguang Zhu ◽  
Li Liu ◽  
Teng Long ◽  
Lei Peng
Keyword(s):  
Latin Hypercube Design ◽  
Latin Hypercube ◽  
Novel Algorithm

scholarly journals A Novel Latin Hypercube Algorithm via Translational Propagation

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Guang Pan ◽  
Pengcheng Ye ◽  
Peng Wang
Keyword(s):  
Computation Time ◽  
Latin Hypercube Design ◽  
Latin Hypercube ◽  
Space Filling ◽  
Enumeration Algorithm ◽  
Latin Hypercube Designs ◽  
Initial Block ◽  
Optimal Latin Hypercube Design ◽  
Computationally Expensive ◽  
Formal Optimization

Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is directly related to the experimental designs used. Optimal Latin hypercube designs are frequently used and have been shown to have good space-filling and projective properties. However, the high cost in constructing them limits their use. In this paper, a methodology for creating novel Latin hypercube designs via translational propagation and successive local enumeration algorithm (TPSLE) is developed without using formal optimization. TPSLE algorithm is based on the inspiration that a near optimal Latin Hypercube design can be constructed by a simple initial block with a few points generated by algorithm SLE as a building block. In fact, TPSLE algorithm offers a balanced trade-off between the efficiency and sampling performance. The proposed algorithm is compared to two existing algorithms and is found to be much more efficient in terms of the computation time and has acceptable space-filling and projective properties.

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