Scalable in-memory mapping of Boolean functions in memristive crossbar array using simulated annealing

2018 ◽  
Vol 89 ◽  
pp. 49-59 ◽  
Author(s):  
Phrangboklang L. Thangkhiew ◽  
Kamalika Datta
Keyword(s):  
Simulated Annealing ◽  
Boolean Functions ◽  
Crossbar Array ◽  
Memory Mapping

Look-ahead mapping of Boolean functions in memristive crossbar array

Integration ◽  
2019 ◽  
Vol 64 ◽  
pp. 152-162 ◽  
Author(s):  
Dev Narayan Yadav ◽  
Phrangboklang L. Thangkhiew ◽  
Kamalika Datta
Keyword(s):  
Boolean Functions ◽  
Crossbar Array ◽  
Look Ahead

THE THERMODYNAMICS OF DYSLEXIC LEARNING

1992 ◽  
Vol 03 (04) ◽  
pp. 351-360
Author(s):  
H. MAKSE ◽  
R.P.J. PERAZZO
Keyword(s):  
Simulated Annealing ◽  
Phase Transitions ◽  
Numerical Analysis ◽  
Boolean Functions ◽  
Schematic Model ◽  
Annealing Schedule ◽  
Nonzero Temperature ◽  
Symmetry Classes ◽  
Cooling Schedule ◽  
Partial Learning

The dyslexic behaviour of a layered network is interpreted as arising from its incomplete training using a cost function that is sensitive to the grouping of Boolean functions into symmetry classes. The training is envisaged as a simulated annealing and a partial learning as the interruption of the cooling schedule at a finite nonzero temperature. We present the thermodynamics of the process. The onset of dyslexic and normal behaviours arise from phase transitions that take place during the annealing schedule. We exemplify the theory with the numerical analysis of a schematic model.

A close examination of distraction in spatial memory: Mapping of the sandwich effect

2009 ◽  
Author(s):  
Katherine Guerard ◽  
Sebastien Tremblay ◽  
Jean Saint-Aubin
Keyword(s):  
Spatial Memory ◽  
Memory Mapping

Penjadwalan Produksi Menggunakan Metode Simulated Annealing pada Unit Produksi Daun Pintu di PT. ML

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Rosnani Ginting ◽  
Chairul Rahmadsyah Manik
Keyword(s):  
Simulated Annealing ◽  
Problem Solving ◽  
Production Scheduling ◽  
Production Control ◽  
Delivery Time ◽  
Production Schedule ◽  
A Company ◽  
Predetermined Time ◽  
Factory Floor

Penjadwalan merupakan aspek yang sangat penting karena didalamnya terdapat elemen perencanaan dan pengendalian produksi bagi suatu perusahaan yang dapat mengirim barang sesuai dengan waktu yang telah ditentukan, untuk memperoleh waktu total penyelesaian yang minimum. Masalah utama yang dihadapi oleh PT. ML adalah keterlambatan penyelesaian order yang mempengaruhi delivery time ke tangan costumer karena pelaksanaan penjadwalan produksi dilantai pabrik belum menghasilkan makespan yang sesuai dengan order yang ada. Oleh kaena itu dituntut untuk mencari solusi pemecahan masalah optimal dalam penentuan jadwal produksi untuk meminimisasi total waktu penyelessaian (makespan) semua order. Dalam penelitian ini, penjadwalan menggunakan metode Simulated Annealing (SA) diharapkan dapat menghasilkan waktu total penyelesaian lebih cepat dari penjadwalan yang ada pada perusahaan.   Scheduling is a very important aspect because in it there are elements of planning and production control for a company that can send goods in accordance with a predetermined time, to obtain a minimum total time of completion. The main problem faced by PT. ML is the delay in completing orders that affect delivery time to customer because the implementation of production scheduling on the factory floor has not produced the makespan that matches the existing order. Therefore, it is required to find optimal problem solving solutions in determining the production schedule to minimize the total time of elimination (makespan) of all orders. In this study, scheduling using the Simulated Annealing (SA) method is expected to produce a total time of completion faster than the existing scheduling in the company.

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