• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4887-4907
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• 2017

Accurate traffic flow forecasting is critical to the development and implementation of city intelligent transportation systems. Therefore, it is one of the most important components in the research of urban traffic scheduling. However, traffic flow forecasting involves a rather complex nonlinear data pattern, particularly during workday peak periods, and a lot of research has shown that traffic flow data reveals a seasonal trend. This paper proposes a new traffic flow forecasting model that combines seasonal relevance vector regression with the hybrid chaotic simulated annealing method (SRVRCSA). Additionally, a numerical example of traffic flow data from The Transportation Data Research Laboratory is used to elucidate the forecasting performance of the proposed SRVRCSA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than the seasonal auto regressive integrated moving average (SARIMA), the double seasonal Holt-Winters exponential smoothing (DSHWES), and the relevance vector regression with hybrid Chaotic Simulated Annealing method (RVRCSA) models. The forecasting performance of RVRCSA with different kernel functions is also studied.

• 대한기계학회논문집
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• 제17권5호
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• pp.1183-1192
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• 1993

본 연구에서는 다음과 같은 두가지 관점에서 공구경로 최적화를 위한 기존 방 법의 문제점을 검토하고 이의 개선 방안을 제시하였다. 첫째, 기존의 공구경로 산출 방법에서는 고려되지 않는 공구대의 공구 장착 현황(turret configuration)이 최적화 과정에서 고려되어야 한다. 둘째로, 제작과 관련한 구속조건(manufacturing con- straints)이 최적화 과정에 직접 반영되어야 한다.

• 한국전자파학회논문지
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• 제15권8호
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• pp.775-780
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• 2004

본 논문은, 각 채널이 여파기와 군지연 등화기로 구성되는, 위성용 다중채널 입력 멀티플렉서에서 사용되는 군지연-등화되는 여파기의, Simulated Annealing(SA) 기법과 Conjugate Gradient(CG) 기법의 새로운 결합형 설계 방식에 의한 구현을 기술한다. SA기법은 8차 타원적분형 여파기, CG기법은 2극 등화기 각각의 회로 설계변수들의 값을 찾아내는데 이용된다. 측정결과는 설계된 부품의 spec.에 대하여 성능이 만족함과 설계기법의 타당성을 나타낸다.

• Journal of Advanced Marine Engineering and Technology
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• 제35권3호
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• pp.341-347
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• 2011

The redundancy allocation problem (RAP) is a famous NP.complete problem that has beenstudied in the system reliability area of ships and airplanes. Recently meta-heuristic techniques have been applied in this topic, for example, genetic algorithms, simulated annealing and tabu search. In particular, tabu search (TS) has emerged as an efficient algorithmic approach for the series-parallel RAP. However, the quality of solutions found by TS depends on the initial solution. As a robust and efficient methodology for the series-parallel RAP, the hybrid metaheuristic (TSA) that is a interactive procedure between the TS and SA (simulated annealing) is developed in this paper. In the proposed algorithm, SA is used to find the diversified promising solutions so that TS can re-intensify search for the solutions obtained by the SA. We test the proposed TSA by the existing problems and compare it with the SA and TS algorithm. Computational results show that the TSA algorithm finds the global optimal solutions for all cases and outperforms the existing TS and SA in cases of 42 and 56 subsystems.

• 대한기계학회논문집A
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• 제26권8호
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• pp.1545-1551
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• 2002

The optical storage device has recently experienced significant improvement, especially for the aspects of high capacity and fast transfer rate. However, it is necessary to study a new shape of air bearing surface for the rotary type actuator because the optical storage device has the lower access time than that of HDD (Hard Disk Drives). In this study, we proposed the air bearing shape by using SA (Simulated Annealing) algorithm which is very effective to achieve the global optimum instead of many local optimums. The objective of optimization is to minimize the deviation in flying height from a target value 100nm. In addition, the pitch and roll angle should be maintained within the operation limits.

• Industrial Engineering and Management Systems
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• 제10권2호
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• pp.134-139
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• 2011

The problem of scheduling in permutation flowshops has been extensively investigated by many researchers. Recently, attempts are being made to consider more than one objective simultaneously and develop algorithms to obtain a set of Pareto-optimal solutions. Varadharajan et al. (2005) presented a multi-objective simulated-annealing algorithm (MOSA) for the problem of permutation-flowshop scheduling with the objectives of minimizing the makespan and the total flowtime of jobs. The MOSA uses two initial sequences obtained using heuristics, and seeks to obtain non-dominated solutions through the implementation of a probability function, which probabilistically selects the objective of minimizing either the makespan or the total flowtime of jobs. In this paper, the same problem of heuristically developing non-dominated sequences is considered. We propose an effective heuristics based on simulated annealing (SA), in which the weighted sum of the makespan and the total flowtime is used. The essences of the heuristics are in selecting the initial sequence, setting the weight and generating a solution in the search process. Using a benchmark problem provided by Taillard (1993), which was used in the MOSA, these conditions are extracted in a large-scale experiment. The non-dominated sets obtained from the existing algorithms and the proposed heuristics are compared. It was found that the proposed heuristics drastically improved the performance of finding the non-dominated frontier.

• 한국컴퓨터그래픽스학회논문지
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• 제4권1호
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• pp.31-40
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• 1998

활성외곽선모델(active contour model)은 물체의 경계를 분할하기 위한 효과적인 방법으로 사용되고 있다. 그런데, 기존 활성외곽선모텔에서는 초기곡선을 분할하고자하는 물체의 경계면에 위치시키고 지역적으로 에너지를 최소화 함에 따라 결과가 초기 곡선의 위치와 형태에 따라 달라지는 단점이 있었다. 본 논문에서는 활성외곽선모델을 B-Spline 곡선에 의해 표현하고, 에너지 최소화 과정에 유전자 알고리즘(Genetic Algorithm: GA)과 시뮬레이티드 어닐링 (Simulated Annealing : SA)을 적용함으로써 기존 활성외곽선모델이 갖는 초기 곡선에 대한 제약성을 개선하고자 했으며, 두가지 방법에 따른 분할 결과와 문제점을 비교하고자 하였다. 제안한 방법의 성능비교를 위하여 이진 합성 영상과 CT 영상, MR 영상을 대상으로 실험을 수행하였다.

• 한국해양공학회지
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• 제17권6호
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• pp.38-46
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• 2003

Aim of this article is to propose Micro-Genetic Simulated Annealing (${\mu}GSA$) as a hybrid metaheuristics approach to find the global optimum of nonlinear optimisation problems. This approach combines the features of modern metaheuristics such as micro-genetic algorithm (${\mu}GAs$) and simulated annealing (SA) with the general robustness of parallel exploration and asymptotic convergence, respectively. Therefore, ${\mu}GSA$ approach can help in avoiding the premature convergence and can search for better global solution, because of its wide spread applicability, global perspective and inherent parallelism. For the superior performance of the ${\mu}GSA$, the five well-know benchmark test functions that were tested and compared with the two global optimisation approaches: scatter search (SS) and hybrid scatter genetic tabu (HSGT) approach. A practical application to structural sandwich panel is also examined by optimism the weight function. From the simulation results, it has been concluded that the proposed ${\mu}GSA$ approach is an effective optimisation tool for soloing continuous nonlinear global optimisation problems in suitable computational time frame.

• Journal of Electrical Engineering and Technology
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• 제6권4호
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• pp.431-438
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• 2011

To ensure that equipment outages do not directly impact the reliability of the ISO-controlled grid, market participants request permission and receive approval for planned outages from the independent system operator (ISO) in competitive electricity markets. In the face of major generation outages, the ISO will make a critical decision as regards the scheduling of the essential maintenance for myriads of generating units over a fixed planning horizon in accordance with security and adequacy assessments. Mainly, we are concerned with a fundamental framework for ISO's maintenance coordination in order to determine precedence of conflicting outages. Simulated annealing, a powerful, general-purpose optimization methodology suitable for real combinatorial search problems, is used. Generally, the ISO will put forward its best effort to adjust individual generator maintenance schedules according to the time preferences of each power generator (GENCO) by taking advantage of several factors such as installed capacity and relative weightings assigned to the GENCOs. Thus, computer testing on a four-GENCO model is conducted to demonstrate the effectiveness of the proposed method and the applicability of the solution scheme to large-scale maintenance scheduling coordination problems.

• 대한산업공학회지
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• 제34권1호
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• pp.98-107
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• 2008

The purpose of this paper is to present an optimization scheme that aims at minimizing the expected cost per unittime. This study considers a linear connected-(r, s)-ouI-of-(m, n):f lattice system whose components are orderedlike the elements of a linear (m, n)-matrix. We assume that all components are in the state 1 (operating) or 0(failed) and identical and s-independent. The system fails whenever at least one connected (r, s)-submatrix offailed components occurs. To find the optimal threshold of maintenance intervention, we use a simulatedannealing(SA) algorithm for the cost optimization procedure. The expected cost per unit time is obtained byMonte Carlo simulation. We also has made sensitivity analysis to the different cost parameters. In this study,utility maintenance model is constructed so that minimize the expense under full equipment policy throughcomparison for the full equipment policy and preventive maintenance policy. The full equipment cycle and unitcost rate are acquired by simulated annealing algorithm. The SA algorithm is appeared to converge fast inmulti-component system that is suitable to optimization decision problem.