• Structural Engineering and Mechanics
• /
• 제43권6호
• /
• pp.771-794
• /
• 2012

This paper presents a multi-objective evolutionary algorithm for combinatorial optimisation and applied for design optimisation of fiber reinforced composite structures. The proposed algorithm closely follows the implementation of Pareto Archive Evolutionary strategy (PAES) proposed in the literature. The modifications suggested include a customized neighbourhood search algorithm in place of mutation operator to improve intensification mechanism and a cross over operator to improve diversification mechanism. Further, an external archive is maintained to collect the historical Pareto optimal solutions. The design constraints are handled in this paper by treating them as additional objectives. Numerical studies have been carried out by solving a hybrid fiber reinforced laminate composite cylindrical shell, stiffened composite cylindrical shell and pressure vessel with varied number of design objectives. The studies presented in this paper clearly indicate that well spread Pareto optimal solutions can be obtained employing the proposed algorithm.

• Journal of Mechanical Science and Technology
• /
• 제20권12호
• /
• pp.2115-2123
• /
• 2006

The paper deals with the identification of Pareto optimal solutions using GA based coevolution in the context of multiobjective optimization. Coevolution is a genetic process by which several species work with different types of individuals in parallel. The concept of cooperative coevolution is adopted to compensate for each of single objective optimal solutions during genetic evolution. The present study explores the GA based coevolution, and develops prescribed and adaptive scheduling schemes to reflect design characteristics among single objective optimization. In the paper, non-dominated Pareto optimal solutions are obtained by controlling scheduling schemes and comparing each of single objective optimal solutions. The proposed strategies are subsequently applied to a three-bar planar truss design and an energy preserving flywheel design to support proposed strategies.

• 정보처리학회논문지B
• /
• 제11B권7호
• /
• pp.841-848
• /
• 2004

진화 알고리즘은 여러 개의 상충하는 목적을 갖는 다목적 최적화 문제를 해결하기에 적합한 방법이다. 특히, 파레토 지배관계에 기초하여 개체의 적합도를 평가하는 파레토 기반 진화알고리즘들은 그 성능에 있어서 비교적 우수한 평가를 받고 있다. 그러나 일반화된 다목적 최적화 진화알고리즘은 복잡한 문제들에서 찾아진 해들의 분포가 전체 파레토 경계면에 대하여 균일하지 못하고 특정 지역에서 집중적으로 해를 생성하는 문제점을 가지고 있다. 본 논문에서 우리는 이러한 문제점을 보완하기 위한 다목적 최적화 진화알고리즘을 제안한다. 제안한 알고리즘은 현재까지 찾아진 최적해들 중 특정 지역에 관중되지 않은 해를 우수 종자로 복제 연산에 참여시킨다. 따라서 특별한 지역탐색 기법을 사용하지 않아도 종자가 되는 개체 주위에 새로운 개체를 생성할 확률이 높기 때문에 지역탐색의 효과를 가질 수 있고, 비교적 고른 분포의 파레토 최적 해를 생성한 수 있다. 5개의 테스트 함수에 대한 실험 결과, 제안한 알고리즘은 모든 문제에서 전체 파레토 경계면에 균일한 분포의 해들을 생성할 수 있었으며, 많은 지역해를 가지는 문제를 제외한 모든 문제에서 NSGA-II보다 우수한 수렴 결과를 보였다.

• 대한조선학회논문집
• /
• 제46권4호
• /
• pp.409-416
• /
• 2009

The structural design problems are acknowledged to be commonly multi-criteria in nature. The various multi-criteria optimization methods are reviewed and the most efficient and easy-to-use Pareto optimal solution methods are applied to structural optimization of a truss and a beam. The result of the study shows that Pareto optimal solution methods can easily be applied to structural optimization with multiple objectives, and the designer can have a choice from those Pareto optimal solutions to meet an appropriate design environment.

• International Journal of Computer Science & Network Security
• /
• 제21권3호
• /
• pp.304-310
• /
• 2021

The paper presents problems of optimization of the synthesis of embedded systems, in particular Pareto optimization. The model of such a system for its design for high-level of abstract is based on the classic approach known from the theory of task scheduling, but it is significantly extended, among others, by the characteristics of tasks and resources as well as additional criteria of optimal system in scope structure and operation. The metaheuristic algorithm operating according to this model introduces a new approach to system synthesis, in which parallelism of task scheduling and resources partition is applied. An algorithm based on a genetic approach with simulated annealing and Boltzmann tournaments, avoids local minima and generates optimized solutions. Such a synthesis is based on the implementation of task scheduling, resources identification and partition, allocation of tasks and resources and ultimately on the optimization of the designed system in accordance with the optimization criteria regarding cost of implementation, execution speed of processes and energy consumption by the system during operation. This paper presents examples and results for multi-criteria optimization, based on calculations for specifying non-dominated solutions and indicating a subset of Pareto solutions in the space of all solutions.

• 한국환경복원기술학회지
• /
• 제27권1호
• /
• pp.45-54
• /
• 2024

This study developed a model to evaluate the co-benefits and trade-off effects between biodiversity and carbon storage capacity based on the implementation locations of nature-based solutions. The model aims to propose optimal implementation locations by using the conceptual idea of edge effects for carbon storage and connectivity for biodiversity. The co-benefits were considered by simultaneously taking into account two effects rather than a single effect. Trade-off effects were observed among optimal plans through a comparison of benefits. The NSGA-II multi-objective optimization algorithm was utilized, confirming the identification of Pareto-optimal solutions. The implementation patterns of Pareto-optimal solutions for green areas were examined. This study holds significance in proposing optimal locations by evaluating various co-benefits and trade-off effects of nature-based solutions. By advancing models based on this evaluation framework, it is anticipated that the assessment of co-benefits and trade-off effects among various benefits of nature-based solutions, such as climate change mitigation, enhancement of biodiversity, and provision of ecosystem services, can be accomplished.

• 한국지능시스템학회논문지
• /
• 제17권7호
• /
• pp.869-874
• /
• 2007

다목적 함수의 최적화 문제(Multiobjective optimization problems)의 경우에는 하나의 최적해가 존재하는 것이 아니라 '파레토 최적해 집합(Pareto optimal set)'이라고 알려진 해들의 집합이 존재한다. 이러한 이상적 파레토 최적해 집합과 가까운 최적해를 찾기 위한 다양한 해탐색 능력은 진화 알고리즘의 성능을 결정한다. 본 논문에서는 게임 모델에 기반한 공진화 알고리즘(GCEA: Game model based Co-Evolutionary Algorithm)에서 해집단의 다양성을 유지하여, 다양한 비지배적 파레토 대안해(non-dominated alternatives)들을 찾기 위한 방법을 제안한다.

• 대한기계학회논문집A
• /
• 제30권11호
• /
• pp.1358-1368
• /
• 2006

This paper proposes a Pareto artificial life algorithm for solving multi-objective optimization problems. The artificial life algorithm for optimization problem with a single objective function is improved to handle Pareto optimization problem through incorporating the new method to estimate the fitness value for a solution and the Pareto list to memorize and to improve the Pareto optimal set. The proposed algorithm was applied to the optimum design of a journal bearing which has two objective functions. The Pareto front and the optimal solution set for the application were presented to give the possible solutions to a decision maker or a designer. Furthermore, the relation between linearly combined single-objective optimization problem and Pareto optimization problem has been studied.

• 에너지공학
• /
• 제13권2호
• /
• pp.128-132
• /
• 2004

본 연구에서는 급전계획의 파레토최적해를 구하는 새로운 방법을 제시하였다. 이를 위하여, 고찰기간에 대해 총 오염물질배출량을 고려하여 최적경제부하배분을 할 수 있는 동적계획법을 도입하였으며, 최적급전계획의 결과를 군으로 얻을 수 있는 파레토최적해를 얻는 방법을 개발하였다. 이 결과, 의사결정자는 파레토최적해를 얻을 수 있으며, 이중에서 하나의 해를 선택하여 사용할 수 있게 되었다. 제안한 방법을 시험계통에 적용하여 유용성을 검증하였다.

• Journal of Electrical Engineering and Technology
• /
• 제3권2호
• /
• pp.218-223
• /
• 2008

A new Pareto-optimal design algorithm, requiring least computational work, is proposed for a single phase AC solenoid actuator with multi-design-objectives: maximizing holding force and minimizing eddy current loss simultaneously. In the algorithm, the design space is successively reduced by a suitable factor, as iteration repeats, with the center of pseudo-optimal point. At each iteration, the objective functions are approximated to a simple second-order response surface with the CCD sampling points generated within the reduced design space, and Pareto-optimal solutions are obtained by applying($1+{\lambda}$) evolution strategy with the fitness values of Pareto strength.