• 제목/요약/키워드: optimisation algorithms

검색결과 17건 처리시간 0.02초

Parameters Influencing the Performance of Ant Algorithms Applied to Optimisation of Buffer Size in Manufacturing

  • Becker, Matthias;Szczerbicka, Helena
    • Industrial Engineering and Management Systems
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    • 제4권2호
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    • pp.184-191
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    • 2005
  • In this article we study the feasibility of the Ant Colony Optimisation (ACO) algorithm for finding optimal Kanban allocations in Kanban systems represented by Stochastic Petri Net (SPN) models. Like other optimisation algorithms inspired by nature, such as Simulated Annealing/Genetic Algorithms, the ACO algorithm contains a large number of adjustable parameters. Thus we study the influence of the parameters on performance of ACO on the Kanban allocation problem, and identify the most important parameters.

Optimal stacking sequence design of laminate composite structures using tabu embedded simulated annealing

  • Rama Mohan Rao, A.;Arvind, N.
    • Structural Engineering and Mechanics
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    • 제25권2호
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    • pp.239-268
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    • 2007
  • This paper deals with optimal stacking sequence design of laminate composite structures. The stacking sequence optimisation of laminate composites is formulated as a combinatorial problem and is solved using Simulated Annealing (SA), an algorithm devised based on inspiration of physical process of annealing of solids. The combinatorial constraints are handled using a correction strategy. The SA algorithm is strengthened by embedding Tabu search in order to prevent recycling of recently visited solutions and the resulting algorithm is referred to as tabu embedded simulated Annealing (TSA) algorithm. Computational performance of the proposed TSA algorithm is enhanced through cache-fetch implementation. Numerical experiments have been conducted by considering rectangular composite panels and composite cylindrical shell with different ply numbers and orientations. Numerical studies indicate that the TSA algorithm is quite effective in providing practical designs for lay-up sequence optimisation of laminate composites. The effect of various neighbourhood search algorithms on the convergence characteristics of TSA algorithm is investigated. The sensitiveness of the proposed optimisation algorithm for various parameter settings in simulated annealing is explored through parametric studies. Later, the TSA algorithm is employed for multi-criteria optimisation of hybrid composite cylinders for simultaneously optimising cost as well as weight with constraint on buckling load. The two objectives are initially considered individually and later collectively to solve as a multi-criteria optimisation problem. Finally, the computational efficiency of the TSA based stacking sequence optimisation algorithm has been compared with the genetic algorithm and found to be superior in performance.

Structural health monitoring through meta-heuristics - comparative performance study

  • Pholdee, Nantiwat;Bureerat, Sujin
    • Advances in Computational Design
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    • 제1권4호
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    • pp.315-327
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    • 2016
  • Damage detection and localisation in structures is essential since it can be a means for preventive maintenance of those structures under service conditions. The use of structural modal data for detecting the damage is one of the most efficient methods. This paper presents comparative performance of various state-of-the-art meta-heuristics for use in structural damage detection based on changes in modal data. The metaheuristics include differential evolution (DE), artificial bee colony algorithm (ABC), real-code ant colony optimisation (ACOR), charged system search (ChSS), league championship algorithm (LCA), simulated annealing (SA), particle swarm optimisation (PSO), evolution strategies (ES), teaching-learning-based optimisation (TLBO), adaptive differential evolution (JADE), evolution strategy with covariance matrix adaptation (CMAES), success-history based adaptive differential evolution (SHADE) and SHADE with linear population size reduction (L-SHADE). Three truss structures are used to pose several test problems for structural damage detection. The meta-heuristics are then used to solve the test problems treated as optimisation problems. Comparative performance is carried out where the statistically best algorithms are identified.

공공부문에서 고용구조의 최적화 : 호주 고용계획을 위한 시스템 다이내믹스 (Optimising Workforce Structure in Public Sector : the System Dynamics of Employment Planning in Australia)

  • 윤영곤;윤경주
    • 산업융합연구
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    • 제15권2호
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    • pp.1-6
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    • 2017
  • 본 논문은 알고리즘을 활용한 최적화를 바탕으로 한 시스템 다이내믹스 피드백 모델을 통해 고용 시뮬레이션의 특징을 제시하는 목적을 가지고 있고 직위, 근무기간, 계급 등의 요소를 중심으로 적정한 고용 인원을 제시하는 3차원 논리적 판단구조를 제공한다. 호주 육군의 고용정책에 대해 보다 신축적인 고용시스템을 제시할 목적으로 시스템 다이내믹스 모델을 통해 국방부의 변화가 심한 정책에 대한 안정적 고용 적정선을 파악한다. 특히 생산성을 최대로 발휘할 수 있는 필요한 고용 패턴 및 외부 인력의 고용, 내부인력의 타 조직으로 이동 등 다양한 가능성을 분석한다.

An advanced machine learning technique to predict compressive strength of green concrete incorporating waste foundry sand

  • Danial Jahed Armaghani;Haleh Rasekh;Panagiotis G. Asteris
    • Computers and Concrete
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    • 제33권1호
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    • pp.77-90
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    • 2024
  • Waste foundry sand (WFS) is the waste product that cause environmental hazards. WFS can be used as a partial replacement of cement or fine aggregates in concrete. A database comprising 234 compressive strength tests of concrete fabricated with WFS is used. To construct the machine learning-based prediction models, the water-to-cement ratio, WFS replacement percentage, WFS-to-cement content ratio, and fineness modulus of WFS were considered as the model's inputs, and the compressive strength of concrete is set as the model's output. A base extreme gradient boosting (XGBoost) model together with two hybrid XGBoost models mixed with the tunicate swarm algorithm (TSA) and the salp swarm algorithm (SSA) were applied. The role of TSA and SSA is to identify the optimum values of XGBoost hyperparameters to obtain the higher performance. The results of these hybrid techniques were compared with the results of the base XGBoost model in order to investigate and justify the implementation of optimisation algorithms. The results showed that the hybrid XGBoost models are faster and more accurate compared to the base XGBoost technique. The XGBoost-SSA model shows superior performance compared to previously published works in the literature, offering a reduced system error rate. Although the WFS-to-cement ratio is significant, the WFS replacement percentage has a smaller influence on the compressive strength of concrete. To improve the compressive strength of concrete fabricated with WFS, the simultaneous consideration of the water-to-cement ratio and fineness modulus of WFS is recommended.

Structural parameter estimation combining domain decomposition techniques with immune algorithm

  • Rao, A. Rama Mohan;Lakshmi, K.
    • Smart Structures and Systems
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    • 제8권4호
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    • pp.343-365
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    • 2011
  • Structural system identification (SSI) is an inverse problem of difficult solution. Currently, difficulties lie in the development of algorithms which can cater to large size problems. In this paper, a parameter estimation technique based on evolutionary strategy is presented to overcome some of the difficulties encountered in using the traditional system identification methods in terms of convergence. In this paper, a non-traditional form of system identification technique employing evolutionary algorithms is proposed. In order to improve the convergence characteristics, it is proposed to employ immune algorithms which are proved to be built with superior diversification mechanism than the conventional evolutionary algorithms and are being used for several practical complex optimisation problems. In order to reduce the number of design variables, domain decomposition methods are used, where the identification process of the entire structure is carried out in multiple stages rather than in single step. The domain decomposition based methods also help in limiting the number of sensors to be employed during dynamic testing of the structure to be identified, as the process of system identification is carried out in multiple stages. A fifteen storey framed structure, truss bridge and 40 m tall microwave tower are considered as a numerical examples to demonstrate the effectiveness of the domain decomposition based structural system identification technique using immune algorithm.

Automatic decomposition of unstructured meshes employing genetic algorithms for parallel FEM computations

  • Rama Mohan Rao, A.;Appa Rao, T.V.S.R.;Dattaguru, B.
    • Structural Engineering and Mechanics
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    • 제14권6호
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    • pp.625-647
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    • 2002
  • Parallel execution of computational mechanics codes requires efficient mesh-partitioning techniques. These mesh-partitioning techniques divide the mesh into specified number of submeshes of approximately the same size and at the same time, minimise the interface nodes of the submeshes. This paper describes a new mesh partitioning technique, employing Genetic Algorithms. The proposed algorithm operates on the deduced graph (dual or nodal graph) of the given finite element mesh rather than directly on the mesh itself. The algorithm works by first constructing a coarse graph approximation using an automatic graph coarsening method. The coarse graph is partitioned and the results are interpolated onto the original graph to initialise an optimisation of the graph partition problem. In practice, hierarchy of (usually more than two) graphs are used to obtain the final graph partition. The proposed partitioning algorithm is applied to graphs derived from unstructured finite element meshes describing practical engineering problems and also several example graphs related to finite element meshes given in the literature. The test results indicate that the proposed GA based graph partitioning algorithm generates high quality partitions and are superior to spectral and multilevel graph partitioning algorithms.

Shipyard Spatial Scheduling Solution using Genetic Algorithms

  • Yoon Duck Young;Ranjan Varghese
    • 한국해양공학회:학술대회논문집
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    • 한국해양공학회 2004년도 학술대회지
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    • pp.35-39
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    • 2004
  • In a shipyard, there exist various critical decision making components pertaining to various production hindrances. The most prominent one is best-fit spatial arrangement for the minimal spatial occupancy with better pick-ability for the erection of the ship in the dock. During the present research, a concept have been conceived to evade the gap between the identification oj inter-relationships among a set of blocks to be included on a pre-erection area, and a detailed graphical layout of their positions, is called an Optimal Block Relationship Diagram A research has been performed on generation of optimal (or near Optimal) that is, with minimal scrap area. An effort has been made in the generation of optimal (or near-optimal) Optimal Block Relationship Diagram with the Goldberg's Genetic Algorithms with a representation and a set of operators are 'trained' specifically for this application. The expected result to date predicts very good solutions to test problems involving innumerable different blocks to place. The suggested algorithm could accept input from an erection sequence generator program which assists the user in defining the nature and strength of the relationships among blocks, and could produce input suitable for use in a detailed layout stage.

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Optimal sensor placement for mode shapes using improved simulated annealing

  • Tong, K.H.;Bakhary, Norhisham;Kueh, A.B.H.;Yassin, A.Y. Mohd
    • Smart Structures and Systems
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    • 제13권3호
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    • pp.389-406
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    • 2014
  • Optimal sensor placement techniques play a significant role in enhancing the quality of modal data during the vibration based health monitoring of civil structures, where many degrees of freedom are available despite a limited number of sensors. The literature has shown a shift in the trends for solving such problems, from expansion or elimination approach to the employment of heuristic algorithms. Although these heuristic algorithms are capable of providing a global optimal solution, their greatest drawback is the requirement of high computational effort. Because a highly efficient optimisation method is crucial for better accuracy and wider use, this paper presents an improved simulated annealing (SA) algorithm to solve the sensor placement problem. The algorithm is developed based on the sensor locations' coordinate system to allow for the searching in additional dimensions and to increase SA's random search performance while minimising the computation efforts. The proposed method is tested on a numerical slab model that consists of two hundred sensor location candidates using three types of objective functions; the determinant of the Fisher information matrix (FIM), modal assurance criterion (MAC), and mean square error (MSE) of mode shapes. Detailed study on the effects of the sensor numbers and cooling factors on the performance of the algorithm are also investigated. The results indicate that the proposed method outperforms conventional SA and Genetic Algorithm (GA) in the search for optimal sensor placement.

Efficient Lambda Logic Based Optimisation Procedure to Solve the Large Scale Generator Constrained Economic Dispatch Problem

  • Adhinarayanan, T.;Sydulu, M.
    • Journal of Electrical Engineering and Technology
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    • 제4권3호
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    • pp.301-309
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    • 2009
  • A simple and efficient Lambda logic (${\lambda}-logic$) based algorithm is proposed for the solution of the generator constrained economic dispatch problem when the generating units having prohibited zones. The proposed method solves the economic dispatch (ED) problem that takes into account ramprate limits, transmission losses and prohibited operating zones in the power system operation. The proposed method uses a simple heuristic rule based on average power of prohibited operating zones which produces the feasibility of solution for the restricted operating units. The effectiveness of the algorithm is tested on five different test systems and the performance compared with other relevant methods reported in the literature. In all the cases, the proposed algorithm performs better than the previous existing algorithms with a less computational burden.