• Title/Summary/Keyword: Heuristic Function

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Development of Potential Function Based Path Planning Algorithm for Mobile Robot

  • Lee, Sang-Il;Kim, Myun-Hee;Oh, Kwang-Seuk;Lee, Sang-Ryong
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2325-2330
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    • 2005
  • A potential field method for solving the problem of path planning based on global and local information for a mobile robot moving among a set of stationary obstacles is described. The concept of various method used path planning is used design a planning strategy. A real human living area is constructed by many moving and imminence obstacles. Home service mobile robot must avoid many obstacles instantly. A path that safe and attraction towards the goal is chosen. The potential function depends on distance from the goal and heuristic function relies on surrounding environments. Three additional combined methods are proposed to apply to human living area, calibration robots position by measured surrounding environment and adapted home service robots. In this work, we proposed the application of various path planning theory to real area, human living. First, we consider potential field method. Potential field method is attractive method, but that method has great problem called local minimum. So we proposed intermediate point in real area. Intermediate point was set in doorframe and between walls there is connect other room or other area. Intermediate point is very efficiency in computing path. That point is able to smaller area, area divided by intermediate point line. The important idea is intermediate point is permanent point until destruction house or apartment house. Second step is move robot with sensing on front of mobile robot. With sensing, mobile robot recognize obstacle and judge moving obstacle. If mobile robot is reach the intermediate point, robot sensing the surround of point. Mobile robot has data about intermediate point, so mobile robot is able to calibration robots position and direction. Third, we gave uncertainty to robot and obstacles. Because, mobile robot was motion and sensing ability is not enough to control. Robot and obstacle have uncertainty. So, mobile robot planed safe path planning to collision free. Finally, escape local minimum, that has possibility occur robot do not work. Local minimum problem solved by virtual obstacle method. Next is some supposition in real living area.

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Optimization of Economic Load Dispatch Problem Using Linearly Approximated Smooth Fuel Cost Function (선형 근사 평활 발전 비용함수를 이용한 경제급전 문제의 최적화)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.3
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    • pp.191-198
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    • 2014
  • This paper proposes a simple linear function approximation method to solve an economic load dispatch problem with complex non-smooth generating cost function. This algorithm approximates a non-smooth power cost function to a linear approximate function and subsequently shuts down a generator with the highest operating cost and reduces the power of generator with more generating cost in order to balance the generating power and demands. When applied to the most prevalent benchmark economic load dispatch cases, the proposed algorithm is found to dramatically reduce the power cost than does heuristic algorithm. Moreover, it has successfully obtained results similar to those obtained through a quadratic approximate function method.

Novel steepest descent adaptive filters derived from new performance function (새로운 성능지수 함수에 대한 직강하 적응필터)

  • 전병을;박동조
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.823-828
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    • 1992
  • A novel steepest descent adaptive filter algorithm, which uses the instantaneous stochastic gradient for the steepest descent direction, is derived from a newly devised performance index function. The performance function for the new algorithm is improved from that for the LMS in consideration that the stochastic steepest descent method is utilized to minimize the performance index iterativly. Through mathematical analysis and computer simulations, it is verified that there are substantial improvements in convergence and misadjustments even though the computational simplicity and the robustness of the LMS algorithm are hardly sacrificed. On the other hand, the new algorithm can be interpreted as a variable step size adaptive filter, and in this respect a heuristic method is proposed in order to reduce the noise caused by the step size fluctuation.

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A novel PSO-based algorithm for structural damage detection using Bayesian multi-sample objective function

  • Chen, Ze-peng;Yu, Ling
    • Structural Engineering and Mechanics
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    • v.63 no.6
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    • pp.825-835
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    • 2017
  • Significant improvements to methodologies on structural damage detection (SDD) have emerged in recent years. However, many methods are related to inversion computation which is prone to be ill-posed or ill-conditioning, leading to low-computing efficiency or inaccurate results. To explore a more accurate solution with satisfactory efficiency, a PSO-INM algorithm, combining particle swarm optimization (PSO) algorithm and an improved Nelder-Mead method (INM), is proposed to solve multi-sample objective function defined based on Bayesian inference in this study. The PSO-based algorithm, as a heuristic algorithm, is reliable to explore solution to SDD problem converted into a constrained optimization problem in mathematics. And the multi-sample objective function provides a stable pattern under different level of noise. Advantages of multi-sample objective function and its superior over traditional objective function are studied. Numerical simulation results of a two-storey frame structure show that the proposed method is sensitive to multi-damage cases. For further confirming accuracy of the proposed method, the ASCE 4-storey benchmark frame structure subjected to single and multiple damage cases is employed. Different kinds of modal identification methods are utilized to extract structural modal data from noise-contaminating acceleration responses. The illustrated results show that the proposed method is efficient to exact locations and extents of induced damages in structures.

A Local Limit Theorem for Large Deviations

  • So, Beong-Soo;Jeon, Jong-Woo
    • Journal of the Korean Statistical Society
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    • v.11 no.2
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    • pp.88-93
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    • 1982
  • A local limit theorem for large deviations for the i.i.d. random variables was given by Richter (1957), who used the saddle point method of complex variables to prove it. In this paper we give an alternative form of local limit theorem for large deviations for the i.i.d. random variables which is essentially equivalent to that of Richter. We prove the theorem by more direct and heuristic method under a rather simple condition on the moment generating function (m.g.f.). The theorem is proved without assuming that $E(X_i)=0$.

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A Study on Flow Shop Scheduling with Early & Tardy Penalty Cost (조기완료 및 납기지연 벌과금을 고려한 흐름작업 시스템의 일정계획)

  • 이정환
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.16 no.27
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    • pp.91-104
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    • 1993
  • This paper is concerned with flow shop scheduling problems having the common due date. V-shape property is used for algorithms with early and tardy penalty cost. The objective of this paper is developing efficient heuristic scheduling algorithms for minimizing total penalty cost function and determining the optimal common due date. The between job delay and the work in process are considered for developing algorithms as penalty cost. Algorithms is simulated to analyze interrelated factors. A numerical example is given for illustrating the proposed algorithms.

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Job-Pair Tardiness Dispatching Rule for Minimize Total Tardiness (납기지연 최소화를 위한 작업상 비교할당규칙)

  • 전태준;박성호
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1998.10a
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    • pp.216-219
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    • 1998
  • This study proposes JPT(Job-Pair Tardiness) that choose operation to be expected to generate better schedule consequence in comparing schedulable operation sets in pair to minimize total tardiness evaluation function in performing scheduling. In result of comparison with existing assignment rules. JPT generates better solution than most other rules in all kinds of problems. So it is anticipated that this is used for initial solution of heuristic and is used for finding more improved solution.

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A Study on Multi-Dimensional Entity Clustering Using the Objective Function of Centroids (중심체 목적함수를 이용한 다차원 개체 CLUSTERING 기법에 관한 연구)

  • Rhee, Chul;Kang, Suk-Ho
    • Journal of the Korean Operations Research and Management Science Society
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    • v.15 no.2
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    • pp.1-15
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    • 1990
  • A mathematical definition of the cluster is suggested. A nonlinear 0-1 integer programming formulation for the multi-dimensional entity clustering problem is developed. A heuristic method named MDEC (Multi-Dimensional Entity Clustering) using centroids and the binary partition is developed and the numerical examples are shown. This method has an advantage of providing bottle-neck entity informations.

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Economic Dispatch Problem Using Advanced Genetic Algorithms (개선된 유전 알고리즘을 이용한 경제급전 문제해석)

  • Park, Jong-Nam;Kim, Jin-O
    • Proceedings of the KIEE Conference
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    • 1997.07c
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    • pp.1106-1108
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    • 1997
  • This paper presents a new approach on genetic algorithms to economic dispatch problem for valve point discontinuities. Proposed approach in this paper on genetic algorithms improves the performance to solve economic dispatch problem for valve point discontinuities through combination in penalty function with death penalty, generation-apart elitism, atavism and heuristic crossover. Numerical results on an actual utility system consisted of 13 thermal units show that the proposed approach is faster and robuster than classical genetic algorithm.

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A Study on Scheduling Considering Delivery and Production Efficiency in the JIT Systems (적시생산시스템에서 납기와 생산효율성을 고려한 Scheduling)

  • Kim, Jung
    • Journal of Industrial Convergence
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    • v.5 no.2
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    • pp.21-32
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    • 2007
  • This paper deals with the sequencing problem in the operation of the manufacturing systems with the constraint of buffer capacity. Some of studies for this theme have been progressed for several years. And then most of them considered only one objective, such as maximum lateness, machine utilization, makespan, mean flowtime and so on. This study deal with two objectives of the delivery for customers and the idle time of machines for producers. For the decision of sequence, the utility function is used. The developed heuristic algorithm presents a good solution. Through a numerical example, the procedures of the job sequencing is explained.

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