Local search metaheuristics ( LSMs ) are efficient methods for solving hard optimization problems in science , engineering , economics and technology . By using LSMs , we could obtain satisfactory resolu ... This paper presents the first application of the renormalized data assimilation method to address this issue . It is associated with a classical optimization algorithm ( simulate annealing ) to solve the combinatory optimization problem consisting of finding the optimal configuration of sensors among a set of potential positions . Three scenarios , corresponding with three different cost functions , are proposed . In this paper , we examine the relationship between netlist structure and the efficiency of placers measured in terms of quality and stability of results . We analyze three types of placers : analytic , simulated-annealing based , and partition based . We have tested these placers on industrial and synthetic benchmarks . In this paper , the personification strategies obtained by observing and learning from the social and nature phenomena are presented . These strategies are generally straightforward and intuitive , and are helpful for the search process jumping out of local minimum , thus allow simulated annealing process to converge fast . These strategies explained how to select variables to flip in each iterative step and how to raise the system temperature when the search process got stuck the local minimum . The algorithm detects , classifies and labels each beat based on morphology . In order to avoid the numerical problems with classical expectation-maximization ( EM ) algorithm we apply a novel method of simulated annealing ( SIM ) for HMM optimization . We show that better results are achieved using simulated annealing approach . Simulated annealing simulation ( SAS ) is a flexible tool for generating stochastic simulations conditioned to data at various scales and precision . However , a number of important drawbacks exists : ( 1 ) SAS requires considerable CPU time , ( 2 ) it requires experience in setting the so-called cooling schedule to obtain convergence , and ( 3 ) its space of uncertainty is not well understood . These formats include patterns , networks , trees , graphs , version spaces , rule sets , equations , and contingency tables . With regard to heuristics , there are a number of generic approaches such as greedy , A * search , tabu search , simulating annealing , and population-based heuristics . The heuristic methods can be applied to a wide class of problems in optimization , classification , statistics , recognition , planning and design . The proposed approaches are based on optimization procedures that use various quality criteria of a feature space as target functions . I investigate the methods based on random search , genetic algorithm , simulation of annealing , as well as the original hybrid algorithm . I presented results of experimental studies of the proposed algorithms on sets of real X-ray images of bone tissue and the lung CT images . The complexity theory solution to e- business [ 18 , 5 ] is defined not only by the simulation of simulated annealing , but also by the unproven need for write-ahead log- ging [ 12 , 4 ] . In this position paper , we ver- ify the refinement of thin clients , demon- strates the robust importance of e-voting technology . Global optimization is a method for finding more reliable models in various fields , such as financial engineering , pattern recognition , process optimization . In this study , we compare and analyze the performance of the state-of-the-art global optimization techniques , which include Genetic Algorithm ( DE , SCGA ) , Simulated Annealing ( ASA , DSSA , SAHPS ) , Tabu & Direct Search ( DTS , DIRECT ) , Deterministic ( MCS , SNOBIT ) , and Trust-Region algorithm . The test functions for the experiments are Benchmark problems in Hedar & Fukushima ( 2004 ) , which are evaluated with respect to efficiency and accuracy . However , since the late 1980s a variety of new approaches for such problems have appeared in the literature . Some of these methods , namely simulated annealing , genetic algorithms , tabu search , the Great Deluge algorithm and the Record-to-Record Travel algorithm , are compared in this paper . These approaches represent not only new algorithms for specific problems , but also new ‘ meta ’ algorithms in the sense that they introduce totally new perspectives on the solution of combinatorial optimization problems . The stage shop is a new extension for the mixed shop problem and as a result , for job shop and open shop problems . In employed bee phase of ABC , a potent neighborhood of the stage shop is used and a tabu search manner is substituted for greedy selection . In onlooker bee phase of ABC , particle swarm optimization idea is applied instead of completely random search . In addition , with the move operations it can also discover more than one RBPs with minimum number of channels including different composition RBPs . A set of criteria are introduced that enhance the Tabu search part of GTS for discovering RBPs . Theorems can provide direct conditions that can state the existence of the necessary criteria of having RBP and RBPs with different composition without considering those criteria . In this work , we investigate Parallel Tabu Searches implemented by competitive agents for the Job Shop problem with Time Lags . The resolution model consists of an Interface Agent and a set of n competitive Job Agents , each one containing the tabu search core , generates an initial solution , executes the tabu search process and uses the NEH heuristic process for the diversification step . Good performances of the proposed model are shown through different comparisons on benchmarks based on instances of the literature . Then we propose an efficient adaptive guidance meta-heuristic algorithm able to solve it . The meta-heuristic determines an initial feasible solution by a Tabu Search step , and next improves this solution by appropriate adaptive guidance mechanisms . The problem is known to be NP-hard , and therefore , we propose heuristics to solve the problem . The proposed heuristics are Tabu search ( Tabu ) , particle swarm optimization ( PSO ) , and self-adaptive differential evolution ( SDE ) . An extensive computational experiment is conducted to compare performances of the proposed heuristics . Then , we prove graph properties useful for the elimination of a priori unfeasible or inferior solutions without direct calculation of cycle time . Based on the established theoretical properties , we propose an approximation algorithm of tabu search type . Empirical tests confirm high efficiency of the algorithm . We introduce a generic decision rule that specifies the next attribute to test at any location in a decision tree . Random searches and tabu searches are applied to determine the best specific form of the rule . The most successful heuristics that we developed are based on the tabu search paradigm . The clustering problem has been studied by many researchers using various approaches , including tabu searching , genetic algorithms , simulated annealing , ant colonies , a hybridized approach , and artificial bee colonies . However , almost none of these approaches have employed the pure particle swarm optimization ( PSO ) technique . Additional energy efficiency is factored into the design by employing guarded evaluation and local clock gating . Our design implements the SA-DCT packing with minimal switching using efficient addressing logic with a transpose memory RAM . The entire design has been synthesized using TSMC 0.09μm TCBN90LP technology yielding a gate count of 12028 for the datapath and its control logic . This paper shows that from the point of view of aliasing errors and the expected values of the wasting test cost caused by misjudging faulty circuits to be fault-free , there are instances where signature analysis with no ( circuit output ) compression(SA-NC ) is preferable to signature analysis with single MISR(SA-MISR ) or multiple input shift registers . It is proposed to apply distortionless sequence compression to the circuit output of SA-NC , which preserves the property of all error detection and yet results in come memory element reduction . Huffman coding and modified Ziv-Lempel coding are promising candidates of distortionless compression when the probabilities of occurrence of input sequences are known and unknown respectively . A method and apparatus for handling an Electronic Service Guide ( ESG ) transmission error in a digital video broadcasting system , including a Service Application ( SA ) entity for receiving a file repair request message from a terminal after broadcasting an ESG from a Service Management ( SM ) entity to the terminal and , when the file repair request message is a request for the ESG , providing the SM entity with the file repair request message and an address of the terminal ; a logical ESG aggregator for generating the ESG within the SM entity interpreting the request message and determining whether to retransmit the ESG to the terminal , and when determining to retransmit the ESG , the logical ESG aggregator delivering , ESG metadata and the address of the terminal to an interactive server for transmitting the ESG within the SM entity . The interactive server transmits the ESG metadata to the terminal . The attributes were entered using the key board . This study shown that digital utility model analyses can not be achieved by looking or carrying out analysis only in one dimensionality of GIS ; need to employ multi-dimensional GIS to accomplish GIS-SA . It has shown how the various dimensionalities of GIS ( 2D , and 3D ) can be used to accomplish specific tasks in multi-purpose utility model such as exchange data in different format and analysis of the utility model at both aggregated of services and disaggregated with data collected by the traditional and modern methods . This technique for improving vestibular signal detection may thus provide additional information to improve strategic abilities . We hypothesize that VSR stimulation will act synergistically with SA training to improve adaptability by increased utilization of vestibular information and therefore serve to optimize and personalize the SA countermeasure prescription . This forms the basis of its usefulness both as a training modality and further help in significantly reducing the number of days required to recover functional performance to preflight levels after long duration space flight . This paper deals with applications of the genetic algorithm ( GA ) and the simulated annealing algorithm ( SA ) to such a combinatorial optimization problem . We clarify the effectiveness of new techniques for applying the GA or SA and the effects of some parameters on GA or SA performance , based on numerical experiments . These results let us determine the parameter tuning of the GA or SA . Our approach uses the same update equations of the conventional FDTD for the adjoint problem , which simplifies the implementation . A self-adjoint approach based on CAVM ( SA-CAVM ) is also proposed to extract the sensitivities of the power reflectivity . Using this self-adjoint approach , only the original simulations are needed to evaluate the objective function and its sensitivities as well . This paper asserts that force commands must define their operational capability requirements in terms of distributed IT services qualified in terms of confidentiality , integrity , and availability . Likewise , CND SA must provide feedback to the command concerning defensive posture , risk , and impact using statements of potential and real reductions in these IT services The OPB-SA effectively compensates for the branch current mismatch due to threshold voltage ( VTH ) offset in SA sensing devices . Extensive simulation results , referring to an industrial hardware-calibrated UMC 65-nm CMOS technology , show that OPB-SA achieves 27.2 , 20 and 11.1 % offset reduction over current latch SA ( CLSA ) , SA with inherent offset cancellation ( SAOC ) and offset-compensated current SA ( OCCSA ) , respectively , without sacrificing performance . The OPB-SA features significant offset suppression capabilities with 31.3 , 12.2 and 7 % tighter offset distribution compared to CLSA , SAOC and OCCSA , respectively . Such features instead can be modelled quite naturally by adopting an agent-oriented perspective . Accordingly , we introduce here a programming model for SOA and Web Services called SA&A ( Service Agents and Artifacts-based Architecture ) , based on a general-purpose conceptual model called A&A ( Agents and Artifacts ) . The approach makes it possible to conceive , design and program services ( and applications using services ) as workspaces where ensemble of proactive activity-oriented entities ( agents ) work together exploiting different kinds of passive function-oriented entities ( artifacts ) used as resources and tools to support their business activities . For models using GloVe embeddings , our syntax - free SA model already achieves a new state - of - the - art by jointly predicting predicates , POS and SRL . LISA with its own parses performs comparably to SA , but when supplied with D & M parses LISA out - performs the previous state - of - the - art by 2.5 F1 points . On the out - of - domain Brown test set , LISA also performs comparably to its syntax - free counterpart with its own parses , but with D & M parses LISA performs exceptionally well , more than 3.5 F1 points higher than he2018jointly . In particular , our three - branch variant ( SiamMask ) significantly outperforms the very recent and top performing DaSiamRPN [ reference ] . Even without box regression branch , our simpler two - branch variant ( SiamMask - 2B ) achieves a high EAO of 0.334 , which is in par with SA Siam R [ reference ] and superior to any other real - time method in the published lit - erature . SiamMask provides a further relative gain of 3.9 % , achieving a EAO of 0.347 , which establishes a new stateof - the - art for real - time tracking .
Local search metaheuristics ( LSMs ) are efficient methods for solving hard optimization problems in science , engineering , economics and technology . By using LSMs , we could obtain satisfactory resolu ...
This paper presents the first application of the renormalized data assimilation method to address this issue . It is associated with a classical optimization algorithm ( simulate annealing ) to solve the combinatory optimization problem consisting of finding the optimal configuration of sensors among a set of potential positions . Three scenarios , corresponding with three different cost functions , are proposed .
In this paper , we examine the relationship between netlist structure and the efficiency of placers measured in terms of quality and stability of results . We analyze three types of placers : analytic , simulated-annealing based , and partition based . We have tested these placers on industrial and synthetic benchmarks .
In this paper , the personification strategies obtained by observing and learning from the social and nature phenomena are presented . These strategies are generally straightforward and intuitive , and are helpful for the search process jumping out of local minimum , thus allow simulated annealing process to converge fast . These strategies explained how to select variables to flip in each iterative step and how to raise the system temperature when the search process got stuck the local minimum .
The algorithm detects , classifies and labels each beat based on morphology . In order to avoid the numerical problems with classical expectation-maximization ( EM ) algorithm we apply a novel method of simulated annealing ( SIM ) for HMM optimization . We show that better results are achieved using simulated annealing approach .
Simulated annealing simulation ( SAS ) is a flexible tool for generating stochastic simulations conditioned to data at various scales and precision . However , a number of important drawbacks exists : ( 1 ) SAS requires considerable CPU time , ( 2 ) it requires experience in setting the so-called cooling schedule to obtain convergence , and ( 3 ) its space of uncertainty is not well understood .
These formats include patterns , networks , trees , graphs , version spaces , rule sets , equations , and contingency tables . With regard to heuristics , there are a number of generic approaches such as greedy , A * search , tabu search , simulating annealing , and population-based heuristics . The heuristic methods can be applied to a wide class of problems in optimization , classification , statistics , recognition , planning and design .
The proposed approaches are based on optimization procedures that use various quality criteria of a feature space as target functions . I investigate the methods based on random search , genetic algorithm , simulation of annealing , as well as the original hybrid algorithm . I presented results of experimental studies of the proposed algorithms on sets of real X-ray images of bone tissue and the lung CT images .
The complexity theory solution to e- business [ 18 , 5 ] is defined not only by the simulation of simulated annealing , but also by the unproven need for write-ahead log- ging [ 12 , 4 ] . In this position paper , we ver- ify the refinement of thin clients , demon- strates the robust importance of e-voting technology .
Global optimization is a method for finding more reliable models in various fields , such as financial engineering , pattern recognition , process optimization . In this study , we compare and analyze the performance of the state-of-the-art global optimization techniques , which include Genetic Algorithm ( DE , SCGA ) , Simulated Annealing ( ASA , DSSA , SAHPS ) , Tabu & Direct Search ( DTS , DIRECT ) , Deterministic ( MCS , SNOBIT ) , and Trust-Region algorithm . The test functions for the experiments are Benchmark problems in Hedar & Fukushima ( 2004 ) , which are evaluated with respect to efficiency and accuracy .
However , since the late 1980s a variety of new approaches for such problems have appeared in the literature . Some of these methods , namely simulated annealing , genetic algorithms , tabu search , the Great Deluge algorithm and the Record-to-Record Travel algorithm , are compared in this paper . These approaches represent not only new algorithms for specific problems , but also new ‘ meta ’ algorithms in the sense that they introduce totally new perspectives on the solution of combinatorial optimization problems .
The stage shop is a new extension for the mixed shop problem and as a result , for job shop and open shop problems . In employed bee phase of ABC , a potent neighborhood of the stage shop is used and a tabu search manner is substituted for greedy selection . In onlooker bee phase of ABC , particle swarm optimization idea is applied instead of completely random search .
In addition , with the move operations it can also discover more than one RBPs with minimum number of channels including different composition RBPs . A set of criteria are introduced that enhance the Tabu search part of GTS for discovering RBPs . Theorems can provide direct conditions that can state the existence of the necessary criteria of having RBP and RBPs with different composition without considering those criteria .
In this work , we investigate Parallel Tabu Searches implemented by competitive agents for the Job Shop problem with Time Lags . The resolution model consists of an Interface Agent and a set of n competitive Job Agents , each one containing the tabu search core , generates an initial solution , executes the tabu search process and uses the NEH heuristic process for the diversification step . Good performances of the proposed model are shown through different comparisons on benchmarks based on instances of the literature .
Then we propose an efficient adaptive guidance meta-heuristic algorithm able to solve it . The meta-heuristic determines an initial feasible solution by a Tabu Search step , and next improves this solution by appropriate adaptive guidance mechanisms .
The problem is known to be NP-hard , and therefore , we propose heuristics to solve the problem . The proposed heuristics are Tabu search ( Tabu ) , particle swarm optimization ( PSO ) , and self-adaptive differential evolution ( SDE ) . An extensive computational experiment is conducted to compare performances of the proposed heuristics .
Then , we prove graph properties useful for the elimination of a priori unfeasible or inferior solutions without direct calculation of cycle time . Based on the established theoretical properties , we propose an approximation algorithm of tabu search type . Empirical tests confirm high efficiency of the algorithm .
We introduce a generic decision rule that specifies the next attribute to test at any location in a decision tree . Random searches and tabu searches are applied to determine the best specific form of the rule . The most successful heuristics that we developed are based on the tabu search paradigm .
The clustering problem has been studied by many researchers using various approaches , including tabu searching , genetic algorithms , simulated annealing , ant colonies , a hybridized approach , and artificial bee colonies . However , almost none of these approaches have employed the pure particle swarm optimization ( PSO ) technique .
Additional energy efficiency is factored into the design by employing guarded evaluation and local clock gating . Our design implements the SA-DCT packing with minimal switching using efficient addressing logic with a transpose memory RAM . The entire design has been synthesized using TSMC 0.09μm TCBN90LP technology yielding a gate count of 12028 for the datapath and its control logic .
This paper shows that from the point of view of aliasing errors and the expected values of the wasting test cost caused by misjudging faulty circuits to be fault-free , there are instances where signature analysis with no ( circuit output ) compression(SA-NC ) is preferable to signature analysis with single MISR(SA-MISR ) or multiple input shift registers . It is proposed to apply distortionless sequence compression to the circuit output of SA-NC , which preserves the property of all error detection and yet results in come memory element reduction . Huffman coding and modified Ziv-Lempel coding are promising candidates of distortionless compression when the probabilities of occurrence of input sequences are known and unknown respectively .
A method and apparatus for handling an Electronic Service Guide ( ESG ) transmission error in a digital video broadcasting system , including a Service Application ( SA ) entity for receiving a file repair request message from a terminal after broadcasting an ESG from a Service Management ( SM ) entity to the terminal and , when the file repair request message is a request for the ESG , providing the SM entity with the file repair request message and an address of the terminal ; a logical ESG aggregator for generating the ESG within the SM entity interpreting the request message and determining whether to retransmit the ESG to the terminal , and when determining to retransmit the ESG , the logical ESG aggregator delivering , ESG metadata and the address of the terminal to an interactive server for transmitting the ESG within the SM entity . The interactive server transmits the ESG metadata to the terminal .
The attributes were entered using the key board . This study shown that digital utility model analyses can not be achieved by looking or carrying out analysis only in one dimensionality of GIS ; need to employ multi-dimensional GIS to accomplish GIS-SA . It has shown how the various dimensionalities of GIS ( 2D , and 3D ) can be used to accomplish specific tasks in multi-purpose utility model such as exchange data in different format and analysis of the utility model at both aggregated of services and disaggregated with data collected by the traditional and modern methods .
This technique for improving vestibular signal detection may thus provide additional information to improve strategic abilities . We hypothesize that VSR stimulation will act synergistically with SA training to improve adaptability by increased utilization of vestibular information and therefore serve to optimize and personalize the SA countermeasure prescription . This forms the basis of its usefulness both as a training modality and further help in significantly reducing the number of days required to recover functional performance to preflight levels after long duration space flight .
This paper deals with applications of the genetic algorithm ( GA ) and the simulated annealing algorithm ( SA ) to such a combinatorial optimization problem . We clarify the effectiveness of new techniques for applying the GA or SA and the effects of some parameters on GA or SA performance , based on numerical experiments . These results let us determine the parameter tuning of the GA or SA .
Our approach uses the same update equations of the conventional FDTD for the adjoint problem , which simplifies the implementation . A self-adjoint approach based on CAVM ( SA-CAVM ) is also proposed to extract the sensitivities of the power reflectivity . Using this self-adjoint approach , only the original simulations are needed to evaluate the objective function and its sensitivities as well .
This paper asserts that force commands must define their operational capability requirements in terms of distributed IT services qualified in terms of confidentiality , integrity , and availability . Likewise , CND SA must provide feedback to the command concerning defensive posture , risk , and impact using statements of potential and real reductions in these IT services
The OPB-SA effectively compensates for the branch current mismatch due to threshold voltage ( VTH ) offset in SA sensing devices . Extensive simulation results , referring to an industrial hardware-calibrated UMC 65-nm CMOS technology , show that OPB-SA achieves 27.2 , 20 and 11.1 % offset reduction over current latch SA ( CLSA ) , SA with inherent offset cancellation ( SAOC ) and offset-compensated current SA ( OCCSA ) , respectively , without sacrificing performance . The OPB-SA features significant offset suppression capabilities with 31.3 , 12.2 and 7 % tighter offset distribution compared to CLSA , SAOC and OCCSA , respectively .
Such features instead can be modelled quite naturally by adopting an agent-oriented perspective . Accordingly , we introduce here a programming model for SOA and Web Services called SA&A ( Service Agents and Artifacts-based Architecture ) , based on a general-purpose conceptual model called A&A ( Agents and Artifacts ) . The approach makes it possible to conceive , design and program services ( and applications using services ) as workspaces where ensemble of proactive activity-oriented entities ( agents ) work together exploiting different kinds of passive function-oriented entities ( artifacts ) used as resources and tools to support their business activities .
For models using GloVe embeddings , our syntax - free SA model already achieves a new state - of - the - art by jointly predicting predicates , POS and SRL . LISA with its own parses performs comparably to SA , but when supplied with D & M parses LISA out - performs the previous state - of - the - art by 2.5 F1 points . On the out - of - domain Brown test set , LISA also performs comparably to its syntax - free counterpart with its own parses , but with D & M parses LISA performs exceptionally well , more than 3.5 F1 points higher than he2018jointly .
In particular , our three - branch variant ( SiamMask ) significantly outperforms the very recent and top performing DaSiamRPN [ reference ] . Even without box regression branch , our simpler two - branch variant ( SiamMask - 2B ) achieves a high EAO of 0.334 , which is in par with SA Siam R [ reference ] and superior to any other real - time method in the published lit - erature . SiamMask provides a further relative gain of 3.9 % , achieving a EAO of 0.347 , which establishes a new stateof - the - art for real - time tracking .
Optimization of parallel iterated local search algorithms on graphics processing unit Optimization Of Sensor Networks For The Estimation Of Atmospheric Pollutants Sources A study of netlist structure and placement efficiency Personification Annealing Algorithm for Solving SAT Problem Morphology analysis of physiological signals using hidden Markov models Automatic Histogram and Variogram Reproduction in Simulated Annealing Simulation Knowledge Discovery Using Heuristics Polynomial feature engineering for classification of textural images Vertex: A Methodology for the Understanding of Fiber-Optic Cables 광역최적화 방법론의 비교 연구 Comparison of the performance of modern heuristics for combinatorial optimization on real data A modified ABC algorithm for the stage shop scheduling problem A Genetic Algorithm and Tabu Search for discovering regular plans in mobile clients Competitive Agents Implementing Parallel Tabu Searches for Job Shop Scheduling Problem with Time Lags Models and algorithms for the empty container repositioning and its integration with routing problems Heuristics for a two-stage assembly flowshop with bicriteria of maximum lateness and makespan Open shop cyclic scheduling Heuristics for efficient classification A particle swarm optimization approach to clustering An optimal adder-based hardware architecture for the DCT/SA-DCT Some analyses on signature analysis with distortionless data compression Method and apparatus for handling an electronic service guide transmission error in a digital video broadcasting system A multi_purpose utility model for Khartoum urban area Using GIS Analysis Techniques Improving Sensorimotor Adaptation Following Long Duration Space Flight by Enhancing Vestibular Information Transfer A Hybrid Method for Block Layout Design based on Metaheuristics. Accurate and efficient sensitivity extraction of complex structures using FDTD Computer Network Defence Situational Awareness Information Requirements An Auto-Calibrated Sense Amplifier with Offset Prediction Approach for Energy-Efficient SRAM An Agent-Oriented Programming Model for SOA & Web Services Linguistically-Informed Self-Attention for Semantic Role Labeling Fast Online Object Tracking and Segmentation: A Unifying Approach
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ISPD ICPR (3) Encyclopedia of Information Science and Technology (III) ICSOFT EA EMNLP 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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