• 제목/요약/키워드: Multi-objective Optimization Problem

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Practical Optimization Methods for Finding Best Recycling Pathways of Plastic Materials

  • Song, Hyun-Seob;Hyun, Jae Chun
    • 청정기술
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    • 제7권2호
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    • pp.99-107
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    • 2001
  • Optimization methodologies have been proposed of find the best environment-friendly recycling pathways of plastic materials based on life-cycle assessment (LCA) methodology. The main difficulty in conducting this optimization study is that multiple environmental burdens have to be considered simultaneously as the cost functions. Instead of generating conservative Pareto or noninferior solutions following multi-objective optimization approaches, we have proposed some practical criteria on how to combine the different environmental burdens into a single measure. The obtained single objective optimization problem can then be solved by conventional nonlinear programming techniques or, more effectively, by a tree search method based on decision flows. The latter method reduces multi-dimensional optimization problems to a set of one-dimensional problems in series. It is expected the suggested tree search approach can be applied to many LCA studies as a new promising optimization tool.

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혼합 교차-엔트로피 알고리즘을 활용한 다수 에이전트-다수 작업 할당 문제 (Multi Agents-Multi Tasks Assignment Problem using Hybrid Cross-Entropy Algorithm)

  • 김광
    • 한국산업정보학회논문지
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    • 제27권4호
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    • pp.37-45
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    • 2022
  • 본 논문에서는 대표적인 조합 최적화(combinatorial optimization) 문제인 다수 에이전트-다수 작업 할당 문제를 제시한다. 할당 문제의 목적은 각 작업의 달성률(achievement rate)의 합을 최대로 하는 에이전트-작업 할당을 결정하는 것이다. 달성률은 각 작업의 할당된 에이전트의 수에 따라 아래 오목 증가(concave down increasing)형태로 다루어지며, 본 할당 문제는 비선형(non-linearity)의 목적함수를 갖는 NP-난해(NP-hard) 문제로 표현된다. 본 논문에서는 할당 문제를 해결하기 위한 효과적이면서 효율적인 문제 해결 방법론으로 혼합 교차-엔트로피 알고리즘(hybrid cross-entropy algorithm)을 제안한다. 일반적인 교차-엔트로피 알고리즘은 문제 상황에 따라 느린 매개변수 업데이트 속도와 조기수렴(premature convergence)이 발생할 수 있다. 본 연구에서 제안하는 문제 해결 방법론은 이러한 단점의 발생 확률을 낮추도록 설계되었으며, 실험적으로도 우수한 성능을 보이는 알고리즘임을 수치실험을 통해 제시한다.

피로수명예측을 위한 반응표면근사화와 순위선호정보를 가진 다기준최적설계에의 응용 (Response Surface Approximation for Fatigue Life Prediction and Its Application to Multi-Criteria Optimization With a Priori Preference Information)

  • 백석흠;조석수;주원식
    • 대한기계학회논문집A
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    • 제33권2호
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    • pp.114-126
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    • 2009
  • In this paper, a versatile multi-criteria optimization concept for fatigue life prediction is introduced. Multi-criteria decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability.

균일분포의 파레토 최적해 생성을 위한 다목적 최적화 진화 알고리즘 (Evolutionary Multi-Objective Optimization Algorithms for Uniform Distributed Pareto Optimal Solutions)

  • 장수현;윤병주
    • 정보처리학회논문지B
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    • 제11B권7호
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    • pp.841-848
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    • 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.

A Multi-objective Optimization Approach to Workflow Scheduling in Clouds Considering Fault Recovery

  • Xu, Heyang;Yang, Bo;Qi, Weiwei;Ahene, Emmanuel
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권3호
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    • pp.976-995
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    • 2016
  • Workflow scheduling is one of the challenging problems in cloud computing, especially when service reliability is considered. To improve cloud service reliability, fault tolerance techniques such as fault recovery can be employed. Practically, fault recovery has impact on the performance of workflow scheduling. Such impact deserves detailed research. Only few research works on workflow scheduling consider fault recovery and its impact. In this paper, we investigate the problem of workflow scheduling in clouds, considering the probability that cloud resources may fail during execution. We formulate this problem as a multi-objective optimization model. The first optimization objective is to minimize the overall completion time and the second one is to minimize the overall execution cost. Based on the proposed optimization model, we develop a heuristic-based algorithm called Min-min based time and cost tradeoff (MTCT). We perform extensive simulations with four different real world scientific workflows to verify the validity of the proposed model and evaluate the performance of our algorithm. The results show that, as expected, fault recovery has significant impact on the two performance criteria, and the proposed MTCT algorithm is useful for real life workflow scheduling when both of the two optimization objectives are considered.

A multi-objective decision making model based on TLBO for the time - cost trade-off problems

  • Eirgash, Mohammad A.;Togan, Vedat;Dede, Tayfun
    • Structural Engineering and Mechanics
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    • 제71권2호
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    • pp.139-151
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    • 2019
  • In a project schedule, it is possible to reduce the time required to complete a project by allocating extra resources for critical activities. However, accelerating a project causes additional expense. This issue is addressed by finding optimal set of time-cost alternatives and is known as the time-cost trade-off problem in the literature. The aim of this study is to identify the optimal set of time-cost alternatives using a multiobjective teaching-learning-based optimization (TLBO) algorithm integrated with the non-dominated sorting concept and is applied to successfully optimize the projects ranging from a small to medium large projects. Numerical simulations indicate that the utilized model searches and identifies optimal / near optimal trade-offs between project time and cost in construction engineering and management. Therefore, it is concluded that the developed TLBO-based multiobjective approach offers satisfactorily solutions for time-cost trade-off optimization problems.

Off-line Multicritera Optimization of Creep Feed Ceramic Grinding Process

  • Chen Ming-Kuen
    • 한국품질경영학회:학술대회논문집
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    • 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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    • pp.680-695
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    • 1998
  • The objective of this study is to optimize the responses of the creep feed ceramic grinding process simultaneously by an off-1ine multicriteria optimization methodology. The responses considered as objectives are material removal rate, flexural strength, normal grinding force, workpiece surface roughness and grinder power. Alumina material was ground by the creep feed grinding mode using superabrasive grinding wheels. The process variables optimized for the above objectives include grinding wheel specification, such as bond type, mesh size, and grit concentration, and grinding process parameters, such as depth of cut and feed rate. A weighting method transforms the multi-objective problem into a single-objective programming format and then, by parametric variation of weights, the set of non-dominated optimum solutions are obtained. Finally, the multi-objective optimization methodology was tested by a sensitivity analysis to check the stability of the model.

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A Transportation Problem with Uncertain Truck Times and Unit Costs

  • Mou, Deyi;Zhao, Wanlin;Chang, Xiaoding
    • Industrial Engineering and Management Systems
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    • 제12권1호
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    • pp.30-35
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    • 2013
  • Motivated by the emergency scheduling in a transportation network, this paper considers a transportation problem, in which, the truck times and transportation costs are assumed as uncertain variables. To meet the demand in the practical applications, two optimization objectives are considered, one is the total costs and another is the completion times. And then, a multi-objective optimization model is developed according to the situation in applications. Because there are commensurability and conflicting between the two objectives commonly, a solution does not necessarily exist that is best with respective to the two objectives. Therefore, the problem is reduced to a single objective model, which is an uncertain programming with a chance-constrain. After some analysis, its equivalent deterministic form is obtained, which is a nonlinear programming. Based on a stepwise optimization strategy, a solution method is developed to solve the problem. Finally, the computational results are provided to demonstrate the effectiveness of our model and algorithm.

Multi-segment curve method를 이용한 선형계획법 기반 최적 조류계산 (A LP-based Optimal Power Flow Using Multi-segment Curve Method)

  • 하동완;김창수;송경빈;백영식
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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    • pp.200-202
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    • 1999
  • This paper describes the optimization problem of real power rescheduling and present an algorithm based linear programming for studying the load-shedding and generation reallocation problem when a portion of the transmission system is disabled and at power flow solution cannot be obtained for the overload of some lines. And in case initial is infeasible, solution could not be converge. So this paper gives an algorithm being lie infeasible quantities within limit. The paper describes a LP-based algorithm to obtain the solution in power dispatch related to overload situations in power system and it is easily extened under various objective. The optimization procedures is based in linear programming with bounded variables and use the multi-segment curve method for a objective function and the validity of the algorithm is verified with two examples : 10-bus system and 57-bus system.

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Multi-objective optimization of submerged floating tunnel route considering structural safety and total travel time

  • Eun Hak Lee;Gyu-Jin Kim
    • Structural Engineering and Mechanics
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    • 제88권4호
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    • pp.323-334
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    • 2023
  • The submerged floating tunnel (SFT) infrastructure has been regarded as an emerging technology that efficiently and safely connects land and islands. The SFT route problem is an essential part of the SFT planning and design phase, with significant impacts on the surrounding environment. This study aims to develop an optimization model considering transportation and structure factors. The SFT routing problem was optimized based on two objective functions, i.e., minimizing total travel time and cumulative strains, using NSGA-II. The proposed model was applied to the section from Mokpo to Jeju Island using road network and wave observation data. As a result of the proposed model, a Pareto optimum curve was obtained, showing a negative correlation between the total travel time and cumulative strain. Based on the inflection points on the Pareto optimum curve, four optimal SFT routes were selected and compared to identify the pros and cons. The travel time savings of the four selected alternatives were estimated to range from 9.9% to 10.5% compared to the non-implemented scenario. In terms of demand, there was a substantial shift in the number of travel and freight trips from airways to railways and roadways. Cumulative strain, calculated based on SFT distance, support structure, and wave energy, was found to be low when the route passed through small islands. The proposed model helps decision-making in the planning and design phases of SFT projects, ultimately contributing to the progress of a safe, efficient, and sustainable SFT infrastructure.