• Title/Summary/Keyword: Simulated Annealing

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Energy-Aware Hybrid Cooperative Relaying with Asymmetric Traffic

  • Chen, Jian;Lv, Lu;Geng, Wenjin;Kuo, Yonghong
    • ETRI Journal
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    • v.37 no.4
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    • pp.717-726
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    • 2015
  • In this paper, we study an asymmetric two-way relaying network where two source nodes intend to exchange information with the help of multiple relay nodes. A hybrid time-division broadcast relaying scheme with joint relay selection (RS) and power allocation (PA) is proposed to realize energy-efficient transmission. Our scheme is based on the asymmetric level of the two source nodes' target signal-to-noise ratio indexes to minimize the total power consumed by the relay nodes. An optimization model with joint RS and PA is studied here to guarantee hybrid relaying transmissions. Next, with the aid of our proposed intelligent optimization algorithm, which combines a genetic algorithm and a simulated annealing algorithm, the formulated optimization model can be effectively solved. Theoretical analyses and numerical results verify that our proposed hybrid relaying scheme can substantially reduce the total power consumption of relays under a traffic asymmetric scenario; meanwhile, the proposed intelligent optimization algorithm can eventually converge to a better solution.

A new method for an automated synthesis of heat exchanger networks (열교환망 자동합성을 위한 새로운 방법)

  • Lee, Gyu-Hwang;Kim, Min-Seok;Lee, In-Beom;Go, Hong-Cheol
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.2
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    • pp.256-263
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    • 1998
  • Among process synthesis problems, the heat exchanger network (HEN) has been subjected to the most concentrated effort because this kind of problems was well defined for solving it and 20-30% energy savings could be realized in the present chemical processes. In this paper, we use an evolutionary approach for HEN synthesis because this approach can overcome the local optimum and combine some heuristic rules. The basic evolutionary approach is composed of three parts, that is, initialization step, growth step and mutation step, as in the simulated annealing and genetic algorithm. This algorithm uses the ecological rule that a better cell will live and worse cell should decompose after repeated generations. With this basic concept, a new procedure is developed and a more efficient method is proposed to generate initial solutions. Its effectiveness is shown using test examples.

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A DFT and QSAR Study of Several Sulfonamide Derivatives in Gas and Solvent

  • Abadi, Robabeh Sayyadi kord;Alizadehdakhel, Asghar;Paskiabei, Soghra Tajadodi
    • Journal of the Korean Chemical Society
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    • v.60 no.4
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    • pp.225-234
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    • 2016
  • The activity of 34 sulfonamide derivatives has been estimated by means of multiple linear regression (MLR), artificial neural network (ANN), simulated annealing (SA) and genetic algorithm (GA) techniques. These models were also utilized to select the most efficient subsets of descriptors in a cross-validation procedure for non-linear -log (IC50) prediction. The results obtained using GA-ANN were compared with MLR-MLR, MLR-ANN, SA-ANN and GA-ANN approaches. A high predictive ability was observed for the MLR-MLR, MLR-ANN, SA-ANN and MLR-GA models, with root mean sum square errors (RMSE) of 0.3958, 0.1006, 0.0359, 0.0326 and 0.0282 in gas phase and 0.2871, 0.0475, 0.0268, 0.0376 and 0.0097 in solvent, respectively (N=34). The results obtained using the GA-ANN method indicated that the activity of derivatives of sulfonamides depends on different parameters including DP03, BID, AAC, RDF035v, JGI9, TIE, R7e+, BELM6 descriptors in gas phase and Mor 32u, ESpm03d, RDF070v, ATS8m, MATS2e and R4p, L1u and R3m in solvent. In conclusion, the comparison of the quality of the ANN with different MLR models showed that ANN has a better predictive ability.

Analysis of trusses by total potential optimization method coupled with harmony search

  • Toklu, Yusuf Cengiz;Bekdas, Gebrail;Temur, Rasim
    • Structural Engineering and Mechanics
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    • v.45 no.2
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    • pp.183-199
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    • 2013
  • Current methods of analysis of trusses depend on matrix formulations based on equilibrium equations which are in fact derived from energy principles, and compatibility conditions. Recently it has been shown that the minimum energy principle, by itself, in its pure and unmodified form, can well be exploited to analyze structures when coupled with an optimization algorithm, specifically with a meta-heuristic algorithm. The resulting technique that can be called Total Potential Optimization using Meta-heuristic Algorithms (TPO/MA) has already been applied to analyses of linear and nonlinear plane trusses successfully as coupled with simulated annealing and local search algorithms. In this study the technique is applied to both 2-dimensional and 3-dimensional trusses emphasizing robustness, reliability and accuracy. The trials have shown that the technique is robust in two senses: all runs result in answers, and all answers are acceptable as to the reliability and accuracy within the prescribed limits. It has also been shown that Harmony Search presents itself as an appropriate algorithm for the purpose.

Meta-Heuristic Algorithms for a Multi-Product Dynamic Lot-Sizing Problem with a Freight Container Cost

  • Kim, Byung-Soo;Lee, Woon-Seek
    • Industrial Engineering and Management Systems
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    • v.11 no.3
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    • pp.288-298
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    • 2012
  • Lot sizing and shipment scheduling are two interrelated decisions made by a manufacturing plant and a third-party logistics distribution center. This paper analyzes a dynamic inbound ordering problem and shipment problem with a freight container cost, in which the order size of multiple products and single container type are simultaneously considered. In the problem, each ordered product placed in a period is immediately shipped by some freight containers in the period, and the total freight cost is proportional to the number of containers employed. It is assumed that the load size of each product is equal and backlogging is not allowed. The objective of this study is to simultaneously determine the lot-sizes and the shipment schedule that minimize the total costs, which consist of production cost, inventory holding cost, and freight cost. Because the problem is NP-hard, we propose three meta-heuristic algorithms: a simulated annealing algorithm, a genetic algorithm, and a new population-based evolutionary meta-heuristic called self-evolution algorithm. The performance of the meta-heuristic algorithms is compared with a local search heuristic proposed by the previous paper in terms of the average deviation from the optimal solution in small size problems and the average deviation from the best one among the replications of the meta-heuristic algorithms in large size problems.

Surrogate Objective based Search Heuristics to Minimize the Number of Tardy Jobs for Multi-Stage Hybrid Flow Shop Scheduling (다 단계 혼합흐름공정 일정계획에서 납기지연 작업 수의 최소화를 위한 대체 목적함수 기반 탐색기법)

  • Choi, Hyun-Seon;Kim, Hyung-Won;Lee, Dong-Ho
    • Journal of Korean Institute of Industrial Engineers
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    • v.35 no.4
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    • pp.257-265
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    • 2009
  • This paper considers the hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. In hybrid flow shops, each job is processed through multiple production stages in series, each of which has multiple identical parallel machines. The problem is to determine the allocation of jobs to the parallel machines at each stage as well as the sequence of the jobs assigned to each machine. Due to the complexity of the problem, we suggest search heuristics, tabu search and simulated annealing algorithms with a new method to generate neighborhood solutions. In particular, to evaluate and select neighborhood solutions, three surrogate objectives are additionally suggested because not much difference in the number of tardy jobs can be found among the neighborhoods. To test the performances of the surrogate objective based search heuristics, computational experiments were performed on a number of test instances and the results show that the surrogate objective based search heuristics were better than the original ones. Also, they gave the optimal solutions for most small-size test instances.

Structural Design for a Jaw Using Metamodels

  • Bang, Il-Kwon;Kang, Dong-Heon;Han, Dong-Seop;Han, Geun-Jo;Lee, Kwon-Hee
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.2
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    • pp.329-334
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    • 2006
  • Rail clamps are mechanical components installed to fix the container crane to its bottoms from wind blast or slip. Rail clamps should be designed to survive the harsh wind loading condition. In this study, the jaw structure that is one part of wedge-typed rail clamp is optimized, considering strength under the severe wind loading condition. According to the classification of structural optimization, the structural optimization of a jaw belongs to shape optimization. In the conventional structural optimization methods, they have difficulties in defining complex shape design variables and preventing mesh distortions. To overcome the difficulties, the metamodel using kriging interpolation method is introduced, replacing true response by approximate one. This research presents the shape optimization of a jaw using iterative kriging interpolation models and simulated annealing algorithm. The new kriging models are iteratively constructed by refining the former kriging models. This process is continued until the convergence criteria are satisfied. The optimum results obtained by the suggested method are compared with those obtained by the DOE (design of experiments) and VT (variation technology) methods built in ANSYS WORKBENCH.

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Comparison of NMR structures refined under implicit and explicit solvents

  • Jee, Jun-Goo
    • Journal of the Korean Magnetic Resonance Society
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    • v.19 no.1
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    • pp.1-10
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    • 2015
  • Refinements with atomistic molecular dynamics (MD) simulation have contributed to improving the qualities of NMR structures. In most cases, the calculations with atomistic MD simulation for NMR structures employ generalized-Born implicit solvent model (GBIS) to take into accounts solvation effects. Developments in algorithms and computational capacities have ameliorated GBIS to approximate solvation effects that explicit solvents bring about. However, the quantitative comparison of NMR structures in the latest GBIS and explicit solvents is lacking. In this study, we report the direct comparison of NMR structures that atomistic MD simulation coupled with GBIS and water molecules refined. Two model proteins, GB1 and ubiquitin, were recalculated with experimental distance and torsion angle restraints, under a series of simulated annealing time steps. Whereas the root mean square deviations of the resulting structures were apparently similar, AMBER energies, the most favored regions in Ramachandran plot, and MolProbity clash scores witnessed that GBIS-refined structures had the better geometries. The outperformance by GBIS was distinct in the structure calculations with sparse experimental restraints. We show that the superiority stemmed, at least in parts, from the inclusion of all the pairs of non-bonded interactions. The shorter computational times with GBIS than those for explicit solvents makes GBIS a powerful method for improving structural qualities particularly under the conditions that experimental restraints are insufficient. We also propose a method to separate the native-like folds from non-violating diverged structures.

Simulation Study of ion-implanted 4H-SiC p-n Diodes (이온주입 공정을 이용한 4H-SiC p-n Diode에 관한 시뮬레이션 연구)

  • Lee, Jae-Sang;Bahng, Wook;Kim, Sang-Cheol;Kim, Nam-Kyun;Koo, Sang-Mo
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.22 no.2
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    • pp.128-131
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    • 2009
  • Silicon carbide (SiC) has attracted significant attention for high frequency, high temperature and high power devices due to its superior properties such as the large band gap, high breakdown electric field, high saturation velocity and high thermal conductivity. We performed Al ion implantation processes on n-type 4H-SiC substrate using a SILVACO ATHENA numerical simulator. The ion implantation model used Monte-Carlo method. We simulated the effect of channeling by Al implantation in both 0 off-axis and 8 off-axis n-type 4H-SiC substrate. We have investigated the effect of varying the implantation energies and the corresponding doses on the distribution of Al in 4H-SiC. The controlled implantation energies were 40, 60, 80, 100 and 120 keV and the implantation doses varied from $2{\times}10^{14}$ to $1{\times}10^{15}\;cm^{-2}$. The Al ion distribution was deeper with increasing implantation energy, whereas the doping level increased with increasing dose. The effect of post-implantation annealing on the electrical properties of Al-implanted p-n junction diode were also investigated.

Stochastic Estimation of Acoustic Impedance of Glass-Reinforced Epoxy Coating

  • Kim, Nohyu;Nah, Hwan-Seon
    • Journal of the Korean Society for Nondestructive Testing
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    • v.34 no.2
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    • pp.119-127
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    • 2014
  • An epoxy coating applied to the concrete surface of a containment building deteriorates in hazardous environments such as those containing radiation, heat, and moisture. Unlike metals, the epoxy coating on a concrete liner absorbs and discharges moisture during the degradations process, so it has a different density and volume during service. In this study, acoustic impedance was adopted for characterizing the degradation of a glass-reinforced epoxy coating using the acoustic reflection coefficient (reflectance) on a rough epoxy coating. For estimating the acoustic reflectance on a wavy epoxy coating surface, a probabilistic model was developed to represent the multiple irregular reflections of the acoustic wave from the wavy surface on the basis of the simulated annealing technique. A number of epoxy-coated concrete specimens were prepared and exposed to accelerated aging conditions to induce an artificial aging degradation in them. The acoustic impedance of the degraded epoxy coating was estimated successfully by minimizing the error between a waveform calculated from the mathematical model and a waveform measured from the surface of the rough coating.