The energy transformation method for the Metropolis algorithm compared with Simulated Annealing

1998 ◽  
Vol 110 (1) ◽  
pp. 69-89 ◽  
Author(s):  
Olivier Catoni
Keyword(s):  
Simulated Annealing ◽  
Transformation Method ◽  
Metropolis Algorithm ◽  
Energy Transformation

OPTIMIZATION OF ENERGY SUPPLY SYSTEMS: SIMULATED ANNEALING VERSUS GENETIC ALGORITHM

2000 ◽  
Vol 11 (04) ◽  
pp. 675-690 ◽  
Author(s):  
LUIS I. GONZALEZ-MONROY ◽  
A. CORDOBA
Keyword(s):  
Genetic Algorithms ◽  
Simulated Annealing ◽  
Energy Supply ◽  
Computation Time ◽  
Efficiency Factor ◽  
Energy Transformation ◽  
Energy Demands ◽  
Supply Systems ◽  
And Storage ◽  
Energy Supply Systems

We have applied two methods (simulated annealing and genetic algorithms) to search the solution of a problem of optimization with constraints in order to determine the best way to fulfill different energy demands using a set of facilities of energy transformation and storage. We have introduced a computational efficiency factor that measures the efficiency of the optimization algorithm and, as a result, we can conclude that for short computation times, genetic algorithms are more efficient than simulated annealing when demand profiles are not very long, whereas the latter is more efficient than the former for long computation time or for big demand profiles.

scholarly journals The Crowding Approach to Niching in Genetic Algorithms

2008 ◽  
Vol 16 (3) ◽  
pp. 315-354 ◽  
Author(s):  
Ole J. Mengshoel ◽  
David E. Goldberg
Keyword(s):  
Genetic Algorithms ◽  
Simulated Annealing ◽  
Analytical Framework ◽  
Metropolis Algorithm ◽  
Classical Genetic ◽  
Wide Range ◽  
The Family ◽  
Tournament Selection

A wide range of niching techniques have been investigated in evolutionary and genetic algorithms. In this article, we focus on niching using crowding techniques in the context of what we call local tournament algorithms. In addition to deterministic and probabilistic crowding, the family of local tournament algorithms includes the Metropolis algorithm, simulated annealing, restricted tournament selection, and parallel recombinative simulated annealing. We describe an algorithmic and analytical framework which is applicable to a wide range of crowding algorithms. As an example of utilizing this framework, we present and analyze the probabilistic crowding niching algorithm. Like the closely related deterministic crowding approach, probabilistic crowding is fast, simple, and requires no parameters beyond those of classical genetic algorithms. In probabilistic crowding, subpopulations are maintained reliably, and we show that it is possible to analyze and predict how this maintenance takes place. We also provide novel results for deterministic crowding, show how different crowding replacement rules can be combined in portfolios, and discuss population sizing. Our analysis is backed up by experiments that further increase the understanding of probabilistic crowding.

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.

Challenges, Concerns, and Perspectives for Poland's Energy Transition during Global COVID-19 Pandemic

2020 ◽  
Vol 1 (2) ◽  
pp. 169-173
Author(s):  
Andrzej Lorkowski ◽  
Robert Jeszke
Keyword(s):  
Internal Energy ◽  
Energy Transition ◽  
Energy Transformation ◽  
Modern Times ◽  
Current Discussion ◽  
The Face ◽  
National Governments ◽  
The Eu ◽  
At Home

The whole world is currently struggling with one of the most disastrous pandemics to hit in modern times – Covid-19. Individual national governments, the WHO and worldwide media organisations are appealing for humanity to universally stay at home, to limit contact and to stay safe in the ongoing fight against this unseen threat. Economists are concerned about the devastating effect this will have on the markets and possible outcomes. One of the countries suffering from potential destruction of this situation is Poland. In this article we will explain how difficult internal energy transformation is, considering the long-term crisis associated with the extraction and usage of coal, the European Green Deal and current discussion on increasing the EU 2030 climate ambitions. In the face of an ongoing pandemic, the situation becomes even more challenging with each passing day.

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