• Title/Summary/Keyword: Genetic Approach

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A Genetic Algorithm Based Approach to the Profitable Tour Problem with Pick-up and Delivery

  • Lee, Hae-Kyeong;Ferdinand, Friska Natalia;Kim, Tai-Oun;Ko, Chang-Seong
    • Industrial Engineering and Management Systems
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    • v.9 no.2
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    • pp.80-87
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    • 2010
  • As express courier market expands rapidly, companies are exposed to fierce competition. To cope with struggle for their survival, they are continuously making efforts to improve their service system. Even if most of service centers are directly linked to a consolidation terminal in courier service network, some of them with regional disadvantages are operated in milk run type from/to the consolidation terminal, which is a traditional PDP (Pick-up and Delivery Problem). This study suggests an approach to solve the PDP with the objective of maximizing the incremental profit, which belongs to PTP (Profitable Tour Problem) class. After the PTP is converted to TSP (Traveling Salesman Problem) with the same objective, a heuristic algorithm based on GA (Genetic Algorithm) is developed and examined through an example problem in practice of a courier service company in Korea.

Two Optimization Techniques for Channel Assignment in Cellular Radio Network (본 논문에서는 신경회로망과 유전자 알고리즘을 이용하여 셀룰러 무선채널 할당을 위한 두 가지 최적화 기법)

  • Nam, In-Gil;Park, Sang-Ho
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.2
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    • pp.439-448
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    • 1999
  • In this paper, two optimization algorithms based on artificial neural networks and genetic algorithms are proposed for cellular radio channel assignment problems. The channel assignment process is characterized as minimization of the energy function which represents constraints of the channel assignment problems. All three constraints such as the co-channel constraint, the adjacent channel constraint and the co-site channel constraint are considered. In the neural networks approach, certain techniques such as the forced assignment and the changing cell order are developed, and in the genetic algorithms approach, data structure and proper genetic operators are developed to find optimal solutions, As simulation results, the convergence rates of the two approaches are presented and compared.

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Current concepts of vascular anomalies

  • Tae Hyung Kim;Jong Woo Choi;Woo Shik Jeong
    • Archives of Craniofacial Surgery
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    • v.24 no.4
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    • pp.145-158
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    • 2023
  • Vascular anomalies encompass a variety of malformations and tumors that can result in severe morbidity and mortality in both adults and children. Advances have been made in the classification and diagnosis of these anomalies, with the International Society for the Study of Vascular Anomalies establishing a widely recognized classification system. In recent years, notable progress has been made in genetic testing and imaging techniques, enhancing our ability to diagnose these conditions. The increasing sophistication of genetic testing has facilitated the identification of specific genetic mutations that help treatment decisions. Furthermore, imaging techniques such as magnetic resonance imaging and computed tomography have greatly improved our capacity to visualize and detect vascular abnormalities, enabling more accurate diagnoses. When considering reconstructive surgery for facial vascular anomalies, it is important to consider both functional and cosmetic results of the procedure. Therefore, a comprehensive multidisciplinary approach involving specialists from dermatology, radiology, and genetics is often required to ensure effective management of these conditions. Overall, the treatment approach for facial vascular anomalies depends on the type, size, location, and severity of the anomaly. A thorough evaluation by a team of specialists can determine the most appropriate and effective treatment plan.

Sire-maternal Grandsire Model and Sire Model in Estimation of Genetic Parameters for Average Daily Gain and Carcass Traits of Japanese Black Cattle

  • Kim, Jong-Bok;Lee, Chaeyoung;Tsuyuki, Tsutomu;Shimogiri, Takeshi;Okamoto, Shin;Maeda, Yoshizane
    • Asian-Australasian Journal of Animal Sciences
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    • v.19 no.12
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    • pp.1678-1684
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    • 2006
  • The objectives of this study were to estimate genetic parameters and sire breeding values for average daily gain (ADG) and carcass traits using sire-maternal grandsire model with REML approach, sire model with REML approach, sire model without relationships among sires and with REML and ANOVA approach, and to investigate advantages and disadvantages of these methods. Data were collected from 42,325 Japanese Black steers and heifers finished and slaughtered from 1991 to 2004. Traits analyzed in this study were average daily gain (ADG) during the fattening period, live weight at slaughter (LW), cold carcass weight (CW), estimated lean yield percentage (LYE), longissimus muscle area (LMA), subcutaneous fat thickness (SFT), rib thickness (RT), and marbling score (BMS). Bivariate analyses were also performed to obtain genetic and phenotypic correlation coefficients among traits. Estimated breeding values were obtained from each model, and simple and rank correlations among breeding values from each model were calculated. Estimates of heritability using the four models ranged from 0.25 to 0.31 in ADG, from 0.21 to 0.24 in LW, from 0.23 to 0.27 in CW, from 0.10 to 0.17 in DP, from 0.40 to 0.42 in LYE, from 0.19 to 0.31 in LMA, from 0.31 to 0.34 in SFT, from 0.26 to 0.33 in RT, and from 0.18 to 0.44 in BMS. The differences in heritability estimates using the four models seemed to be feasible in ADG, CW, DP, LMA, RT, and BMS. Genetic correlation coefficients of ADG with CW, SFT, RT and BMS were moderate to high and positive while the genetic correlation coefficients between ADG and LYE was low and negative. Correlation coefficients of BMS with SFT were negligible for both genetic and phenotypic correlations. The correlations of estimates evaluated from sire models with those from sire-maternal grandsire model were not large enough to convincing that breeding values using a sire model were corresponding to those using a sire-maternal grand sire model. If information of maternal grand sires are not available, the sire model with incomplete pedigree information included only sire of sire (Model 2) is optimal among the sire models evaluated in this study.

Nonlinear Feature Transformation and Genetic Feature Selection: Improving System Security and Decreasing Computational Cost

  • Taghanaki, Saeid Asgari;Ansari, Mohammad Reza;Dehkordi, Behzad Zamani;Mousavi, Sayed Ali
    • ETRI Journal
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    • v.34 no.6
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    • pp.847-857
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    • 2012
  • Intrusion detection systems (IDSs) have an important effect on system defense and security. Recently, most IDS methods have used transformed features, selected features, or original features. Both feature transformation and feature selection have their advantages. Neighborhood component analysis feature transformation and genetic feature selection (NCAGAFS) is proposed in this research. NCAGAFS is based on soft computing and data mining and uses the advantages of both transformation and selection. This method transforms features via neighborhood component analysis and chooses the best features with a classifier based on a genetic feature selection method. This novel approach is verified using the KDD Cup99 dataset, demonstrating higher performances than other well-known methods under various classifiers have demonstrated.

Human-yeast genetic interaction for disease network: systematic discovery of multiple drug targets

  • Suk, Kyoungho
    • BMB Reports
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    • v.50 no.11
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    • pp.535-536
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    • 2017
  • A novel approach has been used to identify functional interactions relevant to human disease. Using high-throughput human-yeast genetic interaction screens, a first draft of disease interactome was obtained. This was achieved by first searching for candidate human disease genes that confer toxicity in yeast, and second, identifying modulators of toxicity. This study found potentially disease-relevant interactions by analyzing the network of functional interactions and focusing on genes implicated in amyotrophic lateral sclerosis (ALS), for example. In the subsequent proof-of-concept study focused on ALS, similar functional relationships between a specific kinase and ALS-associated genes were observed in mammalian cells and zebrafish, supporting findings in human-yeast genetic interaction screens. Results of combined analyses highlighted MAP2K5 kinase as a potential therapeutic target in ALS.

A Method for Screening Product Design Variables for Building A Usability Model : Genetic Algorithm Approach (사용편의성 모델수립을 위한 제품 설계 변수의 선별방법 : 유전자 알고리즘 접근방법)

  • Yang, Hui-Cheol;Han, Seong-Ho
    • Journal of the Ergonomics Society of Korea
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    • v.20 no.1
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    • pp.45-62
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    • 2001
  • This study suggests a genetic algorithm-based partial least squares (GA-based PLS) method to select the design variables for building a usability model. The GA-based PLS uses a genetic algorithm to minimize the root-mean-squared error of a partial least square regression model. A multiple linear regression method is applied to build a usability model that contains the variables seleded by the GA-based PLS. The performance of the usability model turned out to be generally better than that of the previous usability models using other variable selection methods such as expert rating, principal component analysis, cluster analysis, and partial least squares. Furthermore, the model performance was drastically improved by supplementing the category type variables selected by the GA-based PLS in the usability model. It is recommended that the GA-based PLS be applied to the variable selection for developing a usability model.

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Multi-Stage Supply Chain Inventory Control Using Simulation Optimization (시뮬레이션 최적화 방법을 이용한 다단계 공급망 재고 관리)

  • Yoo, Jang-Sun;Kim, Shin-Tae;Hong, Seong-Rok;Kim, Chang-Ouk
    • IE interfaces
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    • v.21 no.4
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    • pp.444-455
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    • 2008
  • In the present manufacturing environment, the appropriate decision making strategy has a significance and it should count on the fast-changing demand of customers. This research derives the optimal levels of the decision variables affecting the inventory related performance in multi-stage supply chain by using simulation and genetic algorithm. Simulation model helps analyze the customer service level of the supply chain computationally and the genetic algorithm searches the optimal solutions by interaction with the simulation model. Our experiments show that the integration approach of the genetic algorithm with a simulation model is effective in finding the solutions that achieve predefined target service levels.

An Enhanced Genetic Algorithm for Global and Local Optimization Search (전역 및 국소 최적화탐색을 위한 향상된 유전 알고리듬의 제안)

  • Kim, Young-Chan;Yang, Bo-Suk
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.6
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    • pp.1008-1015
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    • 2002
  • This paper proposes a combinatorial method to compute the global and local solutions of optimization problem. The present hybrid algorithm is the synthesis of a genetic algorithm and a local concentrate search algorithm (simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm, but also gives a more accurate solution. In addition, this algorithm can find both the global and local optimum solutions. An optimization result is presented to demonstrate that the proposed approach successfully focuses on the advantages of global and local searches. Three numerical examples are also presented in this paper to compare with conventional methods.

Tree Structure Modeling and Genetic Algorithm-based Approach to Unequal-area Facility Layout Problem

  • Honiden, Terushige
    • Industrial Engineering and Management Systems
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    • v.3 no.2
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    • pp.123-128
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    • 2004
  • A tree structure model has been proposed for representing the unequal-area facility layout. Each facility has a different rectangular shape specified by its area and aspect ratio. In this layout problem, based on the assumption that the shop floor has enough space for laying out the facilities, no constraint is considered for a shop floor. Objectives are minimizing total part movement between facilities and total rectangular layout area where all facilities and dead spaces are enclosed. Using the genetic code corresponding to two kinds of information, facility sequence and branching positions in the tree structure model, a genetic algorithm has been applied for finding non-dominated solutions in the two-objective layout problem. We use three kinds of crossover (PMX, OX, CX) for the former part of the chromosome and one-point crossover for the latter part. Two kinds of layout problems have been tested by the proposed method. The results demonstrate that the presented algorithm is able to find good solutions in enough short time.