Relevant bibliographies by topics / Simulated Annealing (SA)

Academic literature on the topic 'Simulated Annealing (SA)'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Simulated Annealing (SA).'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Simulated Annealing (SA)"

1

Siddique, Nazmul, and Hojjat Adeli. "Simulated Annealing, Its Variants and Engineering Applications." International Journal on Artificial Intelligence Tools 25, no. 06 (October 27, 2016): 1630001. http://dx.doi.org/10.1142/s0218213016300015.

Full text
Abstract:
This paper presents a review of research reported on simulated annealing (SA). Different cooling/annealing schedules are summarized. Variants of SA are delineated. Recent applications of SA in engineering are reviewed.
APA, Harvard, Vancouver, ISO, and other styles
2

Yin, Changchun, and Greg Hodges. "Simulated annealing for airborne EM inversion." GEOPHYSICS 72, no. 4 (July 2007): F189—F195. http://dx.doi.org/10.1190/1.2736195.

Full text
Abstract:
The traditional algorithms for airborne electromagnetic (EM) inversion, e.g., the Marquardt-Levenberg method, generally run only a downhill search. Consequently, the model solutions are strongly dependent on the starting model and are easily trapped in local minima. Simulated annealing (SA) starts from the Boltzmann distribution and runs both downhill and uphill searches, rendering the searching process to easily jump out of local minima and converge to a global minimum. In the SA process, the calculation of Jacobian derivatives can be avoided because no preferred searching direction is required as in the case of the traditional algorithms. We apply SA technology for airborne EM inversion by comparing the inversion with a thermodynamic process, and we discuss specifically the SA procedure with respect to model configuration, random walk for model updates, objective function, and annealing schedule. We demonstrate the SA flexibility for starting models by allowing the model parameters to vary in a large range (far away from the true model). Further, we choose a temperature-dependent random walk for model updates and an exponential cooling schedule for the SA searching process. The initial temperature for the SA cooling scheme is chosen differently for different model parameters according to their resolvabilities. We examine the effectiveness of the algorithm for airborne EM by inverting both theoretical and survey data and by comparing the results with those from the traditional algorithms.
APA, Harvard, Vancouver, ISO, and other styles
3

Asrin, Asrin, La Hamimu, and Al Rubaiyn. "Inversi Data Gravitasi Menggunakan Simulated Annealing." Jurnal Rekayasa Geofisika Indonesia 4, no. 03 (November 27, 2022): 141. http://dx.doi.org/10.56099/jrgi.v4i03.28711.

Full text
Abstract:
Inversi data gravitasi penting untuk dilakukan untuk mengetahui model bawah permukaan bumi berdasarkan data anomali medan gravitasi. Inversi data gravitasi dapat dilakukan dengan pendekatan global, Salah satu metode inversi dengan pendekatan global adalah metode simulated annealing (SA). Metode SA ini didasarkan pada analogi proses termodinamika pembentukan kristal suatu substansi. Perkembangannya terinspirasi oleh proses pendinginan logam, dimana struktur kristal energi minimum yang teratur berkembang di dalam logam saat didinginkan secara perlahan dari keadaan panas. Data yang digunakan merupakan data sintetik hasil dari forward modeling untuk menguji keakurasian metode SA. Hasil inversi SA dapat diterapkan dalam menyelesaikan masalah inversi gravitasi dan menunjukkan hasil model inversi yang sesuai dengan model sintetik. Hasil uji coba dengan 2 jenis model sintetik yaitu model persegi dan model patahan menunjukkan nilai misfit estimasi anomali medan gravitasi 2,8 x10-4 mGal untuk model persegi dan 1,7 x 10-4 mGal untuk model patahan. Solusi inversi SA dipengaruhi oleh dua hal, yaitu pembatasan ruang pencarian dan penentuan model tebakan awal.
APA, Harvard, Vancouver, ISO, and other styles
4

Brondani, Marcia De Fatima, Airam Teresa Zago Romcy Sausen, Paulo Sérgio Sausen, and Manuel Osório Binelo. "Battery Model Parameters Estimation Using Simulated Annealing." TEMA (São Carlos) 18, no. 1 (May 22, 2017): 127. http://dx.doi.org/10.5540/tema.2017.018.01.0127.

Full text
Abstract:
In this paper, a Simulated Annealing (SA) algorithm is proposed for the Battery model parametrization, which is used for the mathematical modeling of the Lithium Ion Polymer (LiPo) batteries lifetime. Experimental data obtained by a testbed were used for model parametrization and validation. The proposed SA algorithm is compared to the traditional parametrization methodology that consists in the visual analysis of discharge curves, and from the results obtained, it is possible to see the model efficacy in batteries lifetime prediction, and the proposed SA algorithm efficiency in the parameters estimation.
APA, Harvard, Vancouver, ISO, and other styles
5

Camelo, Pedro Henrique Cardoso, and Rafael Lima De Carvalho. "Multilayer Perceptron optimization through Simulated Annealing and Fast Simulated Annealing." Academic Journal on Computing, Engineering and Applied Mathematics 1, no. 2 (June 10, 2020): 28–31. http://dx.doi.org/10.20873/ajceam.v1i2.9474.

Full text
Abstract:
The Multilayer Perceptron (MLP) is a classic and widely used neural network model in machine learning applications. As the majority of classifiers, MLPs need well-defined parameters to produce optimized results. Generally, machine learning engineers use grid search to optimize the hyper-parameters of the models, which requires to re-train the models. In this work, we show a computational experiment using metaheuristics Simulated Annealing and Fast Simulated Annealing for optimization of MLPs in order to optimize the hyper-parameters. In the reported experiment, the model is used to optimize two parameters: the configuration of the neural network layers and its neuron weights. The experiment compares the best MLPs produced by the SA and FastSA using the accuracy and classifier complexity as comparison measures. The MLPs are optimized in order to produce a classifier for the MNIST database. The experiment showed that FastSA has produced a better MLP, using less computational time and less fitness evaluations.
APA, Harvard, Vancouver, ISO, and other styles
6

Henrique Cardoso Camelo, Pedro, and Rafael Lima De Carvalho. "Multilayer Perceptron optimization through Simulated Annealing and Fast Simulated Annealing." Academic Journal on Computing, Engineering and Applied Mathematics 1, no. 2 (June 10, 2020): 28–31. http://dx.doi.org/10.20873/uft.2675-3588.2020.v1n2.p28-31.

Full text
Abstract:
The Multilayer Perceptron (MLP) is a classic and widely used neural network model in machine learning applications. As the majority of classifiers, MLPs need well-defined parameters to produce optimized results. Generally, machine learning engineers use grid search to optimize the hyper-parameters of the models, which requires to re-train the models. In this work, we show a computational experiment using metaheuristics Simulated Annealing and Fast Simulated Annealing for optimization of MLPs in order to optimize the hyper-parameters. In the reported experiment, the model is used to optimize two parameters: the configuration of the neural network layers and its neuron weights. The experiment compares the best MLPs produced by the SA and FastSA using the accuracy and classifier complexity as comparison measures. The MLPs are optimized in order to produce a classifier for the MNIST database. The experiment showed that FastSA has produced a better MLP, using less computational time and less fitness evaluations.
APA, Harvard, Vancouver, ISO, and other styles
7

Fatyanosa, Tirana Noor, Andreas Nugroho Sihananto, Gusti Ahmad Fanshuri Alfarisy, M. Shochibul Burhan, and Wayan Firdaus Mahmudy. "Hybrid Genetic Algorithm and Simulated Annealing for Function Optimization." Journal of Information Technology and Computer Science 1, no. 2 (February 8, 2017): 82. http://dx.doi.org/10.25126/jitecs.20161215.

Full text
Abstract:
The optimization problems on real-world usually have non-linear characteristics. Solving non-linear problems is time-consuming, thus heuristic approaches usually are being used to speed up the solution’s searching. Among of the heuristic-based algorithms, Genetic Algorithm (GA) and Simulated Annealing (SA) are two among most popular. The GA is powerful to get a nearly optimal solution on the broad searching area while SA is useful to looking for a solution in the narrow searching area. This study is comparing performance between GA, SA, and three types of Hybrid GA-SA to solve some non-linear optimization cases. The study shows that Hybrid GA-SA can enhance GA and SA to provide a better result
APA, Harvard, Vancouver, ISO, and other styles
8

Alkhateeb, Faisal, and Bilal H. Abed-alguni. "A Hybrid Cuckoo Search and Simulated Annealing Algorithm." Journal of Intelligent Systems 28, no. 4 (September 25, 2019): 683–98. http://dx.doi.org/10.1515/jisys-2017-0268.

Full text
Abstract:
Abstract Simulated annealing (SA) proved its success as a single-state optimization search algorithm for both discrete and continuous problems. On the contrary, cuckoo search (CS) is one of the well-known population-based search algorithms that could be used for optimizing some problems with continuous domains. This paper provides a hybrid algorithm using the CS and SA algorithms. The main goal behind our hybridization is to improve the solutions generated by CS using SA to explore the search space in an efficient manner. More precisely, we introduce four variations of the proposed hybrid algorithm. The proposed variations together with the original CS and SA algorithms were evaluated and compared using 10 well-known benchmark functions. The experimental results show that three variations of the proposed algorithm provide a major performance enhancement in terms of best solutions and running time when compared to CS and SA as stand-alone algorithms, whereas the other variation provides a minor enhancement. Moreover, the experimental results show that the proposed hybrid algorithms also outperform some well-known optimization algorithms.
APA, Harvard, Vancouver, ISO, and other styles
9

Du, Gai Li, and Nian Xue. "The Research on Mutil-Objective Location Routing Problem Based on Genetic Simulated Annealing Algorithm." Applied Mechanics and Materials 543-547 (March 2014): 2842–45. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.2842.

Full text
Abstract:
This paper analysis the basic principles of the genetic algorithm (GA) and simulated annealing algorithm (SA) thoroughly. According to the characteristics of mutil-objective location routing problem, the paper designs the hybrid genetic algorithm in various components, and simulate achieved the GSAA (Genetic Simulated Annealing Algorithm).Which architecture makes it possible to search the solution space easily and effectively without overpass computation. It avoids effectively the defects of premature convergence in traditional genetic algorithm, and enhances the algorithms global convergence. Also it improves the algorithms convergence rate to some extent by using the accelerating fitness function. Still, after comparing with GA and SA, the results show that the proposed Genetic Simulated Annealing Algorithm has better search ability. And the emulation experiments show that this method is valid and practicable.
APA, Harvard, Vancouver, ISO, and other styles
10

Alsumairat, Nour, and Mahmoud Alrefaei. "Solving hybrid-vehicle routing problem using modified simulated annealing." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (December 1, 2021): 4922. http://dx.doi.org/10.11591/ijece.v11i6.pp4922-4931.

Full text
Abstract:
<span lang="EN-US">In this paper, we consider the hybrid vehicle routing problem (HVRP) at which the vehicle consumes two types of power: fuel and electricity. The aim of this problem is to minimize the total cost of travelling between customers, provided that each customer is visited only once. The vehicle departs from the depot and returns after completing the whole route. This optimization problem is solved using a modified simulated annealing (SA) heuristic procedure with constant temperature. This approach is implemented on a numerical example and the results are compared with the SA algorithm with decreasing temperature. The obtained results show that using the SA with constant temperature overrides the SA with decreasing temperature. The results indicate that SA with decreasing temperature needs twice the number of iterations needed by the SA with constant temperature to reach a near optimum solution.</span>
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Simulated Annealing (SA)"

1

Kovàcs, Akos. "Solving the Vehicle Routing Problem with Genetic ALgorithm and Simulated Annealing." Thesis, Högskolan Dalarna, Datateknik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:du-3306.

Full text
Abstract:
This Thesis Work will concentrate on a very interesting problem, the Vehicle Routing Problem (VRP). In this problem, customers or cities have to be visited and packages have to be transported to each of them, starting from a basis point on the map. The goal is to solve the transportation problem, to be able to deliver the packages-on time for the customers,-enough package for each Customer,-using the available resources- and – of course - to be so effective as it is possible.Although this problem seems to be very easy to solve with a small number of cities or customers, it is not. In this problem the algorithm have to face with several constraints, for example opening hours, package delivery times, truck capacities, etc. This makes this problem a so called Multi Constraint Optimization Problem (MCOP). What’s more, this problem is intractable with current amount of computational power which is available for most of us. As the number of customers grow, the calculations to be done grows exponential fast, because all constraints have to be solved for each customers and it should not be forgotten that the goal is to find a solution, what is best enough, before the time for the calculation is up. This problem is introduced in the first chapter: form its basics, the Traveling Salesman Problem, using some theoretical and mathematical background it is shown, why is it so hard to optimize this problem, and although it is so hard, and there is no best algorithm known for huge number of customers, why is it a worth to deal with it. Just think about a huge transportation company with ten thousands of trucks, millions of customers: how much money could be saved if we would know the optimal path for all our packages.Although there is no best algorithm is known for this kind of optimization problems, we are trying to give an acceptable solution for it in the second and third chapter, where two algorithms are described: the Genetic Algorithm and the Simulated Annealing. Both of them are based on obtaining the processes of nature and material science. These algorithms will hardly ever be able to find the best solution for the problem, but they are able to give a very good solution in special cases within acceptable calculation time.In these chapters (2nd and 3rd) the Genetic Algorithm and Simulated Annealing is described in details, from their basis in the “real world” through their terminology and finally the basic implementation of them. The work will put a stress on the limits of these algorithms, their advantages and disadvantages, and also the comparison of them to each other.Finally, after all of these theories are shown, a simulation will be executed on an artificial environment of the VRP, with both Simulated Annealing and Genetic Algorithm. They will both solve the same problem in the same environment and are going to be compared to each other. The environment and the implementation are also described here, so as the test results obtained.Finally the possible improvements of these algorithms are discussed, and the work will try to answer the “big” question, “Which algorithm is better?”, if this question even exists.
APA, Harvard, Vancouver, ISO, and other styles
2

Abo, Al Ahad George, and Abbas Salami. "Machine Learning for Market Prediction : Soft Margin Classifiers for Predicting the Sign of Return on Financial Assets." Thesis, Linköpings universitet, Produktionsekonomi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-151459.

Full text
Abstract:
Forecasting procedures have found applications in a wide variety of areas within finance and have further shown to be one of the most challenging areas of finance. Having an immense variety of economic data, stakeholders aim to understand the current and future state of the market. Since it is hard for a human to make sense out of large amounts of data, different modeling techniques have been applied to extract useful information from financial databases, where machine learning techniques are among the most recent modeling techniques. Binary classifiers such as Support Vector Machines (SVMs) have to some extent been used for this purpose where extensions of the algorithm have been developed with increased prediction performance as the main goal. The objective of this study has been to develop a process for improving the performance when predicting the sign of return of financial time series with soft margin classifiers. An analysis regarding the algorithms is presented in this study followed by a description of the methodology that has been utilized. The developed process containing some of the presented soft margin classifiers, and other aspects of kernel methods such as Multiple Kernel Learning have shown pleasant results over the long term, in which the capability of capturing different market conditions have been shown to improve with the incorporation of different models and kernels, instead of only a single one. However, the results are mostly congruent with earlier studies in this field. Furthermore, two research questions have been answered where the complexity regarding the kernel functions that are used by the SVM have been studied and the robustness of the process as a whole. Complexity refers to achieving more complex feature maps through combining kernels by either adding, multiplying or functionally transforming them. It is not concluded that an increased complexity leads to a consistent improvement, however, the combined kernel function is superior during some of the periods of the time series used in this thesis for the individual models. The robustness has been investigated for different signal-to-noise ratio where it has been observed that windows with previously poor performance are more exposed to noise impact.
APA, Harvard, Vancouver, ISO, and other styles
3

Ameli, Mostafa. "Heuristic Methods for Calculating Dynamic Traffic Assignment Simulation-based dynamic traffic assignment: meta-heuristic solution methods with parallel computing Non-unicity of day-to-day multimodal user equilibrium: the network design history effect Improving traffic network performance with road banning strategy: a simulation approach comparing user equilibrium and system optimum." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSET009.

Full text
Abstract:
Les systèmes de transport sont caractérisés de manière dynamique non seulement par des interactions non linéaires entre les différents composants, mais également par des boucles de rétroaction entre l'état du réseau et les décisions des utilisateurs. En particulier, la congestion du réseau impacte à la fois la répartition de la demande locale en modifiant les choix d’itinéraire et la demande multimodale globale. Selon les conditions du réseau, ils peuvent décider de changer, par exemple, leur mode de transport. Plusieurs équilibres peuvent être définis pour les systèmes de transport. L'équilibre de l'utilisateur correspond à la situation dans laquelle chaque utilisateur est autorisé à se comporter de manière égoïste et à minimiser ses propres frais de déplacement. L'optimum du système correspond à une situation où le coût total du transport de tous les utilisateurs est minimal. Dans ce contexte, l’étude vise à calculer les modèles de flux d'itinéraires dans un réseau prenant en compte différentes conditions d’équilibre et à étudier l’équilibre du réseau dans un contexte dynamique. L'étude se concentre sur des modèles de trafic capables de représenter une dynamique du trafic urbain à grande échelle. Trois sujets principaux sont abordés. Premièrement, des méthodes heuristiques et méta-heuristiques rapides sont développées pour déterminer les équilibres avec différents types de trafic. Deuxièmement, l'existence et l'unicité des équilibres d'utilisateurs sont étudiées. Lorsqu'il n'y a pas d'unicité, la relation entre des équilibres multiples est examinée. De plus, l'impact de l'historique du réseau est analysé. Troisièmement, une nouvelle approche est développée pour analyser l’équilibre du réseau en fonction du niveau de la demande. Cette approche compare les optima des utilisateurs et du système et vise à concevoir des stratégies de contrôle afin de déplacer la situation d'équilibre de l'utilisateur vers l'optimum du système
Transport systems are dynamically characterized not only by nonlinear interactions between the different components but also by feedback loops between the state of the network and the decisions of users. In particular, network congestion affects both the distribution of local demand by modifying route choices and overall multimodal demand. Depending on the conditions of the network, they may decide to change for example their transportation mode. Several equilibria can be defined for transportation systems. The user equilibrium corresponds to the situation where each user is allowed to behave selfishly and to minimize his own travel costs. The system optimum corresponds to a situation where the total transport cost of all the users is minimum. In this context, the study aims to calculate route flow patterns in a network considering different equilibrium conditions and study the network equilibrium in a dynamic setting. The study focuses on traffic models capable of representing large-scale urban traffic dynamics. Three main issues are addressed. First, fast heuristic and meta-heuristic methods are developed to determine equilibria with different types of traffic patterns. Secondly, the existence and uniqueness of user equilibria is studied. When there is no uniqueness, the relationship between multiple equilibria is examined. Moreover, the impact of network history is analyzed. Thirdly, a new approach is developed to analyze the network equilibrium as a function of the level of demand. This approach compares user and system optimums and aims to design control strategies in order to move the user equilibrium situation towards the system optimum
APA, Harvard, Vancouver, ISO, and other styles
4

Dahal, Keshav P., G. M. Burt, J. R. McDonald, and S. J. Galloway. "GA/SA-based hybrid techniques for the scheduling of generator maintenance in power systems." 2000. http://hdl.handle.net/10454/952.

Full text
Abstract:
Yes
Proposes the application of a genetic algorithm (GA) and simulated annealing (SA) based hybrid approach for the scheduling of generator maintenance in power systems using an integer representation. The adapted approach uses the probabilistic acceptance criterion of simulated annealing within the genetic algorithm framework. A case study is formulated in this paper as an integer programming problem using a reliability-based objective function and typical problem constraints. The implementation and performance of the solution technique are discussed. The results in this paper demonstrate that the technique is more effective than approaches based solely on genetic algorithms or solely on simulated annealing. It therefore proves to be a valid approach for the solution of generator maintenance scheduling problems
APA, Harvard, Vancouver, ISO, and other styles

Books on the topic "Simulated Annealing (SA)"

1

Simulated Annealing (Sa and Optimization : Modern Algorithms With Vlsi, Optimal Design, and Missile Defense Applications). American Sciences Press, Inc., 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Simulated Annealing (SA)"

1

Wendt, Oliver. "Simulated Annealing (SA)." In Tourenplanung durch Einsatz naturanaloger Verfahren, 115–36. Wiesbaden: Deutscher Universitätsverlag, 1995. http://dx.doi.org/10.1007/978-3-663-09046-5_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Castillo, Pedro A., Juan J. Merelo, Jesús González, Víctor Rivas, and Gustavo Romero. "SA-prop: Optimization of multilayer perceptron parameters using simulated annealing." In Lecture Notes in Computer Science, 661–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0098224.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Senent, Juan S., Miguel A. Martinez, Xavier Blasco, and Javier Sanchis. "MIMO predictive control of temperature and humidity inside a greenhouse using simulated annealing (SA) as optimizer of a multicriteria index." In Tasks and Methods in Applied Artificial Intelligence, 271–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-64574-8_413.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Ray, Sujay. "Adaptive Simulated Annealing Algorithm to Solve Bio-Molecular Optimization." In Handbook of Research on Natural Computing for Optimization Problems, 475–89. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0058-2.ch020.

Full text
Abstract:
Energy minimization is a paramount zone in the field of computational and structural biology for protein modeling. It helps in mending distorted geometries in the folded functional protein by moving its atoms to release internal constraints. It attempts to hold back to zero value for the net atomic force on every atom. But to overcome certain disadvantages in energy minimization, Simulated Annealing (SA) can be helpful. SA is a molecular dynamics technique, where temperature is gradually reduced during the simulation. It provides the best configuration of bio-molecules in shorter time. With the advancement in computational knowledge, one essential but less sensitive variant of SA: Adaptive Simulated Annealing (ASA) algorithm is beneficial, because it automatically adjusts the temperature scheme and abrupt opting of step. Therefore it benefits to prepare stable protein models and further to investigate protein-protein interactions. Thus, a residue-level study can be analyzed in details for the benefit of the entire biota.
APA, Harvard, Vancouver, ISO, and other styles
5

Liñán-García, Ernesto, Helue I. De la Barrera-Gómez, Ana Laura Vázquez-Esquivel, Jesús Aguirre-García, Andrea Isabel Cervantes-Payan, Edgar Osvaldo Escobedo-Hernández, and Luis A. López-Alday. "Solving Vehicle Routing Problem With Multi-Phases Simulated Annealing Algorithm." In Handbook of Research on Emergent Applications of Optimization Algorithms, 508–30. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2990-3.ch022.

Full text
Abstract:
In this chapter, a new multi-phases meta-heuristic algorithm based on Simulated Annealing(SA) is proposed in order to solve the Capacitated Vehicle Routing Problem (CVRP) with stochastic demands. This algorithm is named Multi-Phases Simulated Annealing (MPSA), which has four phases of annealing, which are Fast Quenching Phase (FQP), the Annealing Boltzmann Phase (ABP), the Bose-Einstein Annealing Phase (BEAP), and the Dynamical Equilibrium Phase (DEP). These four phases are applied in different ranges of temperature in the Simulated Annealing. The proposed algorithm is applied to generate very close to optimal solution for a cleaning distribution company. Proposed approach is focused to the Vehicle Routing Problem with homogeneous capacities and stochastic demands to gain solutions where routes are the most economical, so based on this, the proposed algorithm is applied to solve the limited Capacity Vehicle Routing Problem (CVRP), trying to provide more effective and efficient metaheuristics.
APA, Harvard, Vancouver, ISO, and other styles
6

Haque, Khan Md Ariful, and M. Ahsan Akhtar Hasin. "Fuzzy Based Project Time-Cost Optimization Using Simulated Annealing Search Technique." In Civil and Environmental Engineering, 1473–86. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9619-8.ch067.

Full text
Abstract:
The Project time-cost optimization is inherently a complex task. Because of various kinds of uncertainties, such as weather, productivity level, inflation, human factors etc. during project execution process, time and cost of each activity may vary significantly. The complexity multiplies several folds when the operational times are not deterministic, rather fuzzy in nature. Therefore, deterministic models for time-cost optimization are not yet efficient. It is very difficult to find the exact solution of savings in both time and cost. To make such problems realistic, triangular fuzzy numbers and the concept of a-cut method in fuzzy logic theory are employed to model the problem. Because of NP-hard nature of the project scheduling problem, this paper develops a simple approach with Simulated Annealing (SA) based searching technique. The proposed model leads the decision makers to choose the desired solution under different values of a-cut. Finally, taking a real project, the performance of SA has been tested.
APA, Harvard, Vancouver, ISO, and other styles
7

Santo, Rafael do Espírito, Roseli de Deus Lopes, and Rangaraj M. Rangayyan. "Classification of Breast Masses in Mammograms Using Radial Basis Functions and Simulated Annealing." In Transdisciplinary Advancements in Cognitive Mechanisms and Human Information Processing, 239–49. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-60960-553-7.ch014.

Full text
Abstract:
We present pattern classification methods based upon nonlinear and combinational optimization techniques, specifically, radial basis functions (RBF) and simulated annealing (SA), to classify masses in mammograms as malignant or benign. Combinational optimization is used to pre-estimate RBF parameters, namely, the centers and spread matrix. The classifier was trained and tested, using the leave-one-out procedure, with shape, texture, and edge-sharpness measures extracted from 57 regions of interest (20 related to malignant tumors and 37 related to benign masses) manually delineated on mammograms by a radiologist. The classifier’s performance, with pre-estimation of the parameters, was evaluated in terms of the area Az under the receiver operating characteristics curve. Values up to Az = 0.9997 were obtained with RBF-SA with pre-estimation of the centers and spread matrix, which are better than the results obtained with pre-estimation of only the RBF centers, which were up to 0.9470. Overall, the results with the RBF-SA method were better than those provided by standard multilayer perceptron neural networks
APA, Harvard, Vancouver, ISO, and other styles
8

Yaghin, Reza Ghasemy, Hadi Mosadegh, and S. M. T. Fatemi Ghomi. "Differential Return on Investment Optimization." In Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems, 189–211. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2944-6.ch009.

Full text
Abstract:
A two-echelon supply chain is studied that involves a retailer who faces demand from two or more market segments and enable to set different prices and marketing expenditures and a supplier who desires to find optimal number of shipments through an integrated system. A new mixed-integer non-linear fractional programming (MINLFP) model is developed. In order to solve the resultant MINLFP model, the constrained non-linear programming model is reformulated as an unconstrained one using penalty terms. Two meta-heuristics, namely simulated annealing (SA) and imperialist competitive algorithm (ICA), are applied to solve the relaxed unconstrained model. Numerical results show that ICA can reach better solutions in comparison with SA. However, SA has the ability of providing more robust solutions which are converged to a good solution. The chapter concludes with superiority of SA.
APA, Harvard, Vancouver, ISO, and other styles
9

Niroomand, Sadegh, Ali Mahmoodirad, and Saber Molla-Alizadeh-Zavardehi. "Single Batch-Processing Machine Scheduling Problem with Fuzzy Due-Dates." In Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics, 751–69. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9644-0.ch028.

Full text
Abstract:
This paper focuses on a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in existence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS) and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms.
APA, Harvard, Vancouver, ISO, and other styles
10

Mukherjee, Soumen, Arunabha Adhikari, and Madhusudan Roy. "Melanoma Identification Using MLP With Parameter Selected by Metaheuristic Algorithms." In Intelligent Innovations in Multimedia Data Engineering and Management, 241–68. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7107-0.ch010.

Full text
Abstract:
Nature-inspired metaheuristic algorithms find near optimum solutions in a fast and efficient manner when used in a complex problem like finding optimum number of neurons in hidden layers of a multi-layer perceptron (MLP). In this chapter, a classification work is discussed of malignant melanoma, which is a type of lethal skin cancer. The classification accuracy is more than 91% with visually imperceptible features using MLP. The results found are comparably better than the related work found in the literature. Finally, the performance of two metaheuristic algorithms (i.e., particle swarm optimization [PSO] and simulated annealing [SA]) are compared and analyzed with different parameters to show their searching nature in the two-dimensional search space of hidden layer neurons.
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Simulated Annealing (SA)"

1

Aly, Sherif, Madara M. Ogot, and Richard Pelz. "An Improved Simulated Annealing Algorithm for Optimal Design." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0056.

Full text
Abstract:
Abstract A new algorithm based on the simulated annealing (SA) optimization algorithm is presented. This approach, simulated annealing with random search iterative improvement (SAWI), essentially initiates the SA process to locate the neighborhood of the global optimum. Prior to the convergence of SA, the algorithm switches to random search iterative improvement, a local search method, to converge to the optimum. The key to the effectiveness of SAWI is identifying when the premature termination of SA should occur. This paper presents the results of a parametric study conducted on the transition parameter, illustrating the effects of delayed and premature transition to the local search method, on the final solution. Two examples are presented and discussed to illustrate the efficacy of the algorithm. The results of these examples demonstrate that SAWI makes significant reductions in computation time while maintaining the simplicity of the original SA algorithm and without loss in quality of solution.
APA, Harvard, Vancouver, ISO, and other styles
2

Cantelmi, Frank J., Richard B. Pelz, and Madara M. Ogot. "A Generic Cooling Schedule for Simulated Annealing." In ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/dac-14247.

Full text
Abstract:
Abstract Discrete-State Simulated Annealing (DSSA) is a version of Simulated Annealing (SA) having a generic cooling schedule which is totally independent of the problem being optimized. By employing a generic cooling schedule, DSSA does not incur the overhead computational costs associated with the tuning of the parameters that make up the cooling schedule. DSSA introduces a single parameter that sets the total number of discrete states available. This paper summarizes the algorithm and presents results for two studies. First, the performance of the DSSA algorithm is compared to that of a parameter-tuned SA algorithm. The DSSA algorithm is able to provide similar results without any parameter tuning. Second, a parameter study is undertaken to determine the effect of varying the total number of discrete states. The results suggest that the performance of the algorithm is insensitive to the total number of states.
APA, Harvard, Vancouver, ISO, and other styles
3

Rodrigues, Rance, and Sandip Kundu. "Model based double patterning lithography (DPL) and simulated annealing (SA)." In 2011 International Symposium on Quality Electronic Design (ISQED). IEEE, 2011. http://dx.doi.org/10.1109/isqed.2011.5770754.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Yang, Xinghao, Weifeng Liu, Dacheng Tao, and Wei Liu. "BESA: BERT-based Simulated Annealing for Adversarial Text Attacks." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/453.

Full text
Abstract:
Modern Natural Language Processing (NLP) models are known immensely brittle towards text adversarial examples. Recent attack algorithms usually adopt word-level substitution strategies following a pre-computed word replacement mechanism. However, their resultant adversarial examples are still imperfect in achieving grammar correctness and semantic similarities, which is largely because of their unsuitable candidate word selections and static optimization methods. In this research, we propose BESA, a BERT-based Simulated Annealing algorithm, to address these two problems. Firstly, we leverage the BERT Masked Language Model (MLM) to generate contextual-aware candidate words to produce fluent adversarial text and avoid grammar errors. Secondly, we employ Simulated Annealing (SA) to adaptively determine the word substitution order. The SA provides sufficient word replacement options via internal simulations, with an objective to obtain both a high attack success rate and a low word substitution rate. Besides, our algorithm is able to jump out of local optima with a controlled probability, making it closer to achieve the best possible attack (i.e., the global optima). Experiments on five popular datasets manifest the superiority of BESA compared with existing methods, including TextFooler, BAE, BERT-Attack, PWWS, and PSO.
APA, Harvard, Vancouver, ISO, and other styles
5

Nemirsky, Kristofer Kevin, and Kamran Turkoglu. "Simulated Annealing-Based Optimal PID Controller Design: A Case Study on Nonlinear Quadcopter Dynamics." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5121.

Full text
Abstract:
In this thesis, the history and evolution of rotor aircraft with simulated annealing-based PID application were reviewed and quadcopter dynamics are presented. The dynamics of a quadcopter were then modeled, analyzed, and linearized. A cascaded loop architecture with PID controllers was used to stabilize the plant dynamics, which was improved upon through the application of simulated annealing (SA). A Simulink model was developed to test the controllers and verify the functionality of the proposed control system design. In addition, the data that the Simulink model provided were compared with flight data to present the validity of derived dynamics as a proper mathematical model representing the true dynamics of the quadcopter system. Then, the SA-based global optimization procedure was applied to obtain optimized PID parameters. It was observed that the tuned gains through the SA algorithm produced a better performing PID controller than the original manually tuned one. Next, we investigated the uncertain dynamics of the quadcopter setup. After adding uncertainty to the gyroscopic effects associated with pitch-and-roll rate dynamics, the controllers were shown to be robust against the added uncertainty. A discussion follows to summarize SA-based algorithm PID controller design and performance outcomes. Lastly, future work on SA application on multi-input-multi-output (MIMO) systems is briefly discussed.
APA, Harvard, Vancouver, ISO, and other styles
6

Ma, G. H., F. Zhang, Y. F. Zhang, and A. Y. C. Nee. "An Automated Process Planning System Based on Genetic Algorithm and Simulated Annealing." In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/detc2002/dfm-34159.

Full text
Abstract:
The paper presents the development of a computer-aided process planning (CAPP) system based on Genetic Algorithm (GA) and Simulated Annealing (SA). The system employs an optimization modeling method that generates all the feasible operation-method alternatives. It also provides flexible optimization criteria that will satisfy the various needs from different job-shops and/or job-batches. Two search algorithms based on GA and SA respectively have been developed to solve the problem effectively. Also, the system provides manufacturability analysis function, which gives designers and job shop operators helpful information about the manufacturing.
APA, Harvard, Vancouver, ISO, and other styles
7

Ramzi, Zouaoui. "The construction of sequences for identification of digital circuits using simulated annealing (SA)." In 2014 Information and Communication Technologies Innovation and Application (ICTIA). IEEE, 2014. http://dx.doi.org/10.1109/ictia.2014.7883611.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

"A Comprehensive Tuning of Distillation Column Composition Controllers using Simulated Annealing Algorithm (SA)." In International Conference on Artificial Intelligence, Energy and Manufacturing Engineering. International Institute of Engineers, 2014. http://dx.doi.org/10.15242/iie.e0614035.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Ghazi, R., and H. Kamal. "Optimal size and placement of DVR's in distribution system using simulated annealing (SA)." In 18th International Conference and Exhibition on Electricity Distribution (CIRED 2005). IEE, 2005. http://dx.doi.org/10.1049/cp:20051364.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Gheisari, Soulmaz, Abolfazl T. Haghighat, and Saman saadat. "SA-Mobicast: A simulated annealing-based mobicast routing protocol for wireless sensor networks." In 2008 3rd International Symposium on Wireless Pervasive Computing (ISWPC). IEEE, 2008. http://dx.doi.org/10.1109/iswpc.2008.4556264.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Simulated Annealing (SA)' for particular source types:
Journal articles
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography