• Title/Summary/Keyword: flexible search algorithm

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Process Planning in Flexible Assembly Systems Using a Symbiotic Evolutionary Algorithm (공생 진화알고리듬을 이용한 유연조립시스템의 공정계획)

  • Kim, Yeo-Keun;Euy, Jung-Mi;Shin, Kyoung-Seok;Kim, Yong-Ju
    • IE interfaces
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    • v.17 no.2
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    • pp.208-217
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    • 2004
  • This paper deals with a process planning problem in the flexible assembly system (FAS). The problem is to assign assembly tasks to stations with limited working space and to determine assembly routing with the objective of minimizing transfer time of the products among stations, while satisfying precedence relations among the tasks and upper-bound workload constraints for each station. In the process planning of FAS, the optimality of assembly routing depends on tasks loading. The integration of tasks loading and assembly routing is therefore important for an efficient utilization of FAS. To solve the integrated problem at the same time, in this paper we propose a new method using an artificial intelligent search technique, named 2-leveled symbiotic evolutionary algorithm. Through computational experiments, the performance of the proposed algorithm is compared with those of a traditional evolutionary algorithm and a symbiotic evolutionary algorithm. The experimental results show that the proposed algorithm outperforms the algorithms compared.

Search Range Reduction Algorithm with Motion Vectors of Upper Blocks for HEVC (상위 블록 움직임 벡터를 이용한 HEVC 움직임 예측 탐색 범위 감소 기법)

  • Lee, Kyujoong
    • Journal of Korea Multimedia Society
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    • v.21 no.1
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    • pp.18-25
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    • 2018
  • In High Efficiency Video Coding (HEVC), integer motion estimation (IME) requires a large amount of computational complexity because HEVC adopts the high flexible and hierarchical coding structures. In order to reduce the computational complexity of IME, this paper proposes the search range reduction algorithm, which takes advantage of motion vectors similarity between different layers. It needs only a few modification for HEVC reference software. Based on the experimental results, the proposed algorithm reduces the processing time of IME by 28.1% on average, whereas its the $Bj{\emptyset}ntegaard$ delta bitrate (BD-BR) increase is 0.15% which is negligible.

A Multiobjective Process Planning of Flexible Assembly Systems with Evolutionary Algorithms (진화알고리듬을 이용한 유연조립시스템의 다목적 공정계획)

  • Shin, Kyoung Seok;Kim, Yeo Keun
    • Journal of Korean Institute of Industrial Engineers
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    • v.31 no.3
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    • pp.180-193
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    • 2005
  • This paper deals with a multiobjective process planning problem of flexible assembly systems(FASs). The FAS planning problem addressed in this paper is an integrated one of the assignment of assembly tasks to stations and the determination of assembly routing, while satisfying precedence relations among the tasks and flexibility capacity for each station. In this research, we consider two objectives: minimizing transfer time of the products among stations and absolute deviation of workstation workload(ADWW). We place emphasis on finding a set of diverse near Pareto or true Pareto optimal solutions. To achieve this, we present a new multiobjective coevolutionary algorithm for the integrated problem here, named a multiobjective symbiotic evolutionary algorithm(MOSEA). The structure of the algorithm and the strategies of evolution are devised in this paper to enhance the search ability. Extensive computational experiments are carried out to demonstrate the performance of the proposed algorithm. The experimental results show that the proposed algorithm is a promising method for the integrated and multiobjective problem.

A Flexible Search Algorithm for Block Motion Estimation (블록 기반 움직임 추정을 위한 유연한 탐색 알고리즘)

  • Jeong, Chang-Uk;Kim, Jong-Ho;Choi, Jin-Ku;Kim, Yong-Deak
    • Proceedings of the IEEK Conference
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    • 2005.11a
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    • pp.501-504
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    • 2005
  • 블록 정합 기법(block matching algorithm, BMA) 중에서 가장 널리 알려진 3 단계 탐색(three-step search, 3SS) 알고리즘은 큰 움직임 추정에 적합하지만 고정된 탐색 점으로 인하여 작은 움직임 추정에는 계산 면에서 낭비가 심하고 탐색이 잘못될 경우가 대부분이다. 한편, 효율적인 3 단계 탐색(efficient three-step search, E3SS)은 중앙-편중된 움직임 추정을 작은 다이아몬드 탐색(small diamond search, SDS) 알고리즘으로 보완하여 예측성과 탐색 속도를 향상시킨 알고리즘이다. 본 논문에서는 탐색 초기 단계에서 탐색 점을 최적 배치하고 E3SS 의 SDS 알고리즘을 변형시킨 탐색 알고리즘을 제안한다. 실험 결과는 제안된 탐색 알고리즘이 E3SS 와 비교하여 평균 22% 정도 계산량을 감소시키면서도 MSE(Mean Square Error)의 성능 저하를 거의 보이지 않는 것으로 나타난다.

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A Flexible Branch and Bound Method for the Job Shop Scheduling Problem

  • Morikawa, Katsumi;Takahashi, Katsuhiko
    • Industrial Engineering and Management Systems
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    • v.8 no.4
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    • pp.239-246
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    • 2009
  • This paper deals with the makespan minimization problem of job shops. The problem is known as one of hard problems to optimize, and therefore, many heuristic methods have been proposed by many researchers. The aim of this study is also to propose a heuristic scheduling method for the problem. However, the difference between the proposed method and many other heuristics is that the proposed method is based on depth-first branch and bound, and thus it is possible to find an optimal solution at least in principle. To accelerate the search, when a node is judged hopeless in the search tree, the proposed flexible branch and bound method can indicate a higher backtracking node. The unexplored nodes are stored and may be explored later to realize the strict optimization. Two methods are proposed to generate the backtracking point based on the critical path of the current best feasible schedule, and the minimum lower bound for the makespan in the unexplored sub-problems. Schedules are generated based on Giffler and Thompson's active schedule generation algorithm. Acceleration of the search by the flexible branch and bound is confirmed by numerical experiment.

Ranking Methods of Web Search using Genetic Algorithm (유전자 알고리즘을 이용한 웹 검색 랭킹방법)

  • Jung, Yong-Gyu;Han, Song-Yi
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.10 no.3
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    • pp.91-95
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    • 2010
  • Using artificial neural network to use a search preference based on the user's information, the ranking of search results that will enable flexible searches can be improved. After trained in several different queries by other users in the past, the actual search results in order to better reflect the use of artificial neural networks to neural network learning. In order to change the weights constantly moving backward in the network to change weights of backpropagation algorithm. In this study, however, the initial training, performance data, look for increasing the number of lessons that can be overfitted. In this paper, we have optimized a lot of objects that have a strong advantage to apply genetic algorithms to the relevant page of the search rankings flexible as an object to the URL list on a random selection method is proposed for the study.

Multi-Stage Cold Forging Process Design with A* Searching Algorithm (탐색 알고리즘을 이용한 냉간 단조 공정 설계)

  • 김홍석;임용택
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 1995.10a
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    • pp.30-36
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    • 1995
  • Conventionally design for multi-stage cold forging depends on the designer's experience and decision-making. Due to such non-deterministic nature of the process sequence design, a flexible inference engine is needed for process design expert system. In this study, A* searching algorithm was introduced to arrive at the vetter process sequence design considering the number of forming stages and levels of effective strain, effective stress, and forming load during the porcess. In order to optimize the process sequence in producing the final part, cost function was defined and minimized using the proposed A* searching algorithm. For verification of the designed forming sequences, forming experiments and finite element analyses were carried out in the present investigation. The developed expert system using A* searching algorithm can produce a flexible design system based on changes in the number of forming stages and weights.

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Job Route Selection Expert System for Workload Balancing in Flexible Flow Line (유연생산라인의 부하평준화를 위한 작업흐름선택 전문가시스템)

  • 함호상;한성배
    • Journal of Intelligence and Information Systems
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    • v.2 no.1
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    • pp.93-107
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    • 1996
  • A flexible flow line(FFL) consists of several groups of identical machines. All work-orders flow along the same path through successive machine groups. Thus, we emphasized the balancing of workloads between machine groups in order to maximize total productivity. On the other hand, many different types of work-orders, in varying batch or lot sizes, are produced simultaneously. The mix of work-orders, their lot sizes, and the sequence in which they are produced affect the amount of workload. However, the work-orders and their lot sizes are prefixed and cannot be changed. Because of these reasons, we have developed an optimal route selection model using heuristic search and Min-Max algorithm for balancing the workload between machine groups in the FFL.

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A 3-D Genetic Algorithm for Finding the Number of Vehicles in VRPTW

  • Paik, Si-Hyun;Ko, Young-Min;Kim, Nae-Heon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.22 no.53
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    • pp.37-44
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    • 1999
  • The problem to be studied here is the minimization of the total travel distance and the number of vehicles used for delivering goods to customers. Vehicle routes must also satisfy a variety of constraints such as fixed vehicle capacity, allowed operating time. Genetic algorithm to solve the VRPTW with heterogeneous fleet is presented. The chromosome of the proposed GA in this study has the 3-dimension. We propose GA that has the cubic-chromosome for VRPTW with heterogeneous fleet. The newly suggested ‘Cubic-GA (or 3-D GA)’ in this paper means the 2-D GA with GLS(Genetic Local Search) algorithms and is quite flexible. To evaluate the performance of the algorithm, we apply it to the Solomon's VRPTW instances. It produces a set of good routes and the reasonable number of vehicles.

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Solving the Constrained Job Sequencing Problem using Candidate Order based Tabu Search (후보순위 기반 타부 서치를 이용한 제약 조건을 갖는 작업 순서결정 문제 풀이)

  • Jeong, Sung-Wook;Kim, Jun-Woo
    • The Journal of Information Systems
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    • v.25 no.1
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    • pp.159-182
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    • 2016
  • Purpose This paper aims to develop a novel tabu search algorithm for solving the sequencing problems with precedence constraints. Due to constraints, the traditional meta heuristic methods can generate infeasible solutions during search procedure, which must be carefully dealt with. On the contrary, the candidate order based tabu search (COTS) is based on a novel neighborhood structure that guarantees the feasibility of solutions, and can dealt with a wide range of sequencing problems in flexible manner. Design/methodology/approach Candidate order scheme is a strategy for constructing a feasible sequence by iteratively appending an item at a time, and it has been successfully applied to genetic algorithm. The primary benefit of the candidate order scheme is that it can effectively deal with the additional constraints of sequencing problems and always generates the feasible solutions. In this paper, the candidate order scheme is used to design the neighborhood structure, tabu list and diversification operation of tabu search. Findings The COTS has been applied to the single machine job sequencing problems, and we can see that COTS can find the good solutions whether additional constraints exist or not. Especially, the experiment results reveal that the COTS is a promising approach for solving the sequencing problems with precedence constraints. In addition, the operations of COTS are intuitive and easy to understand, and it is expected that this paper will provide useful insights into the sequencing problems to the practitioners.