• 한국산업융합학회 논문집
• /
• 제27권2_2호
• /
• pp.467-473
• /
• 2024

Metaheuristics' impact is profound across many fields, yet domestic financial portfolio optimization research falls short, particularly in asset allocation. This study delves into metaheuristics for portfolio optimization, examining theoretical and practical benefits. Findings indicate portfolios optimized via metaheuristics outperform the Dow Jones Index in Sharpe ratios, underscoring their potential to enhance risk-adjusted returns significantly. Tabu search, in comparison to Simulated Annealing, demonstrates superior performance by efficiently navigating the search space. Despite these advancements, practical application remains challenging due to the complexities in metaheuristic implementation. The study advocates for broader algorithmic exploration, including population-based metaheuristics, to refine asset allocation strategies further. This research marks a step towards optimizing portfolios from an extensive array of financial assets, aiming for maximum efficacy in investment outcomes.

• 한국해양공학회지
• /
• 제17권6호
• /
• pp.38-46
• /
• 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.

• 한국공간구조학회논문집
• /
• 제21권2호
• /
• pp.89-97
• /
• 2021

This paper describes an adaptive hybrid evolutionary firefly algorithm for a topology optimization of truss structures. The truss topology optimization problems begins with a ground structure which is composed of all possible nodes and members. The optimization process aims to find the optimum layout of the truss members. The hybrid metaheuristics are then used to minimize the objective functions subjected to static or dynamic constraints. Several numerical examples are examined for the validity of the present method. The performance results are compared with those of other metaheuristic algorithms.

• 산업공학
• /
• 제24권4호
• /
• pp.281-294
• /
• 2011

This paper considers the rail crane scheduling problem which is defined as determining the sequence of loading/unloading container on/from a freight train. The objective is to minimize the weighted sum of the range of order completion time and makespan. The range of order completion time implies the difference between the maximum of completion time and minimum of start time of each customer order consisting of jobs. Makespan refers to the time when all the jobs are completed. In a rail freight terminal, logistics firms as a customer wish to reduce the range of their order completion time. To develop a methodology for the crane scheduling, we formulate the problem as a mixed integer program and develop three metaheuristics, namely, genetic algorithm, simulated annealing, and tabu search. To validate the effectiveness of heuristic algorithms, computational experiments are done based on a set of real life data. Results of the experiments show that heuristic algorithms give good solutions for small-size and large-size problems in terms of solution quality and computation time.

• Structural Engineering and Mechanics
• /
• 제77권3호
• /
• pp.417-439
• /
• 2021

The geometric nonlinearity has been successfully integrated with the design of steel structural system. Thus, the tubular lattice girder, one application of steel structural systems have already been optimized to obtain an economic design following the completion of computationally expensive design procedure. In order to decrease its computing cost, this study proposes to employ five multi-objective metaheuristics for the design optimization of geometrically nonlinear tubular lattice girder. Then, the employed multi-objective optimization algorithms (MOAs), NSGAII, PESAII, SPEAII, AbYSS and MoCell are evaluated considering their computing performances. For an unbiased evaluation of their computing performance, a tubular lattice girder with varying size-shape-topology and a benchmark truss design with 17 members are not only optimized considering the geometrically nonlinear behavior, but three benchmark mathematical functions along with the four benchmark linear design problems are also included for the comparison purpose. The proposed experimental study is carried out by use of an intelligent optimization tool named JMetal v5.10. According to the quantitative results of employed quality indicators with respect to a statistical analysis test, MoCell is resulted with an achievement of showing better computing performance compared to other four MOAs. Consequently, MoCell is suggested as an optimization tool for the design of geometrically nonlinear tubular lattice girder than the other employed MOAs.

• 한국콘텐츠학회:학술대회논문집
• /
• 한국콘텐츠학회 2014년도 춘계 종합학술대회 논문집
• /
• pp.35-36
• /
• 2014

• 정보처리학회논문지B
• /
• 제16B권5호
• /
• pp.411-426
• /
• 2009

대부분의 메타휴리스틱들은 동물의 행동을 모방한 것이다. 본 논문에서는 Mine 알고리즘을 제안한다. Mine 알고리즘(Mine Algorithm)은 인간의 행동을 모방한 메타휴리스틱이다. 탐색의 관점에서 인간의 노하우와 휴리스틱이 가장 잘 녹아 있는 업종은 광산업(mining industry)이다. Mine 알고리즘에서는 광산 업무에 초점을 맞추어서 인간의 행동패턴을 형식화한다. Mine 알고리즘은 다양한 탐색기법을 유연하게 구사하며, 그 때문에 광범위한 문제에서 고른 성능을 보인다. 즉, 범용성이 양호하다. 우리는 기존 메타휴리스틱들과의 비교 실험을 통하여 Mine 알고리즘의 개선된 범용성을 보인다.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2003년도 추계학술발표논문집 (상)
• /
• pp.119-122
• /
• 2003

본 논문에서는 분산메모리 멀티프로세서 시스템에서 태스크와 프로세서 노드간의 매핑에 관한 최적화 문제를 메타휴리스틱스(metatheuristics)의 장점을 효과적으로 결합한 새로운 방안을 소개한다. 태스크-프로세서 할당에 있어 부하균형을 고려한 MFA-GA 하이브리드 알고리즘을 제안하고 기존의 할당 방안들과 성능실험을 통해 비교 분석한다. 우리의 합성 휴리스틱을 이용하면 각 방법을 단독으로 사용하는 것 보다 매핑 품질과 수행시간 면에서 개선된 성능결과를 얻을 수 있음을 보여주었다.

• Industrial Engineering and Management Systems
• /
• 제7권3호
• /
• pp.204-213
• /
• 2008

Companies that produce capital goods need to schedule the production of products that have complex product structures with components that require many operations on different machines. A feasible schedule must satisfy operation and assembly precedence constraints. It is also important to avoid deadlock situations. In this paper a Genetic Algorithm (GA) has been developed that includes a new repair process that rectifies infeasible schedules that are produced during the evolution process. The algorithm was designed to minimise the combination of earliness and tardiness penalties and took into account finite capacity constraints. Three different sized problems were obtained from a collaborating capital goods company. A design of experimental approach was used to systematically identify that the best genetic operators and GA parameters for each size of problem.

• Journal of Advanced Marine Engineering and Technology
• /
• 제38권10호
• /
• pp.1340-1346
• /
• 2014

Previous studies of reliable server assignment considered only to assign the same cost of server, that is, homogeneous servers. In this paper, we generally deal with reliable server assignment with different server costs, i.e., heterogeneous servers. We formulate this problem as a nonlinear integer programming mathematically. Our problem is defined as determining a deployment of heterogeneous servers to maximize a measure of service availability. We propose two metaheuristic algorithms (tabu search and particle swarm optimization) for solving the problem of reliable server assignment. From the computational results, we notice that our tabu search outstandingly outperforms particle swarm optimization for all test problems. In terms of solution quality and computing time, the proposed method is recommended as a promising metaheuristic for a kind of reliability optimization problems including reliable sever assignment and e-Navigation system.