• Title/Summary/Keyword: Constrained Optimization

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Research of a freedom rate for timetabling problem (시간표 작성 문제의 자유도에 관한 연구)

  • An, Jong-Il;Jo, Seung-Han
    • Journal of the Korea Computer Industry Society
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    • v.10 no.5
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    • pp.201-206
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    • 2009
  • The timetabling problem is a one of the optimization problem for satisfied a constraints. Most optimization algorithm arrives optimal to use a method that is make a initial solution and modify and reconstruct it repetitively. In case of insufficient resources, it is not easy to obtain initial solution oneself. The most method of make a initial solution is high constrained subject assign first. The freedom rate is a numerical value of degree of how much constrained. In this paper, we define the freedom rate in timetabling problem and experiment its role in timetabling process.

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Generation and Animation of Optimal Robot Joint Motion data using Captured Human Motion data (인체모션 데이터 획득 장치와 최적화 기법을 사용한 로봇운동 데이터 생성과 애니메이션)

  • Bae, Tae Young;Kim, Young Seog
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.22 no.3_1spc
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    • pp.558-565
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    • 2013
  • This paper describes a whole-body (human body's) motion generation scheme for an android robot that uses motion capture device and a nonlinear constrained optimization method. Because the captured motion data are based on global coordinates and the actors have different heights and different upper-lower body ratios, the captured motion data cannot be used directly for a humanoid robot. In this paper, we suggest a method for obtaining robot joint angles, which allow the resultant robot motion to be as close as possible to the captured human motion data, by applying a nonlinear constrained optimization method. In addition, the results are animated to demonstrate the similarity of the motions.

AN ACTIVE SET SQP-FILTER METHOD FOR SOLVING NONLINEAR PROGRAMMING

  • Su, Ke;Yuan, Yingna;An, Hui
    • East Asian mathematical journal
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    • v.28 no.3
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    • pp.293-303
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    • 2012
  • Sequential quadratic programming (SQP) has been one of the most important methods for solving nonlinear constrained optimization problems. Recently, filter method, proposed by Fletcher and Leyffer, has been extensively applied for its promising numerical results. In this paper, we present and study an active set SQP-filter algorithm for inequality constrained optimization. The active set technique reduces the size of quadratic programming (QP) subproblem. While by the filter method, there is no penalty parameter estimate. Moreover, Maratos effect can be overcome by filter technique. Global convergence property of the proposed algorithm are established under suitable conditions. Some numerical results are reported in this paper.

SCHEDULING REPETITIVE PROJECTS WITH STOCHASTIC RESOURCE CONSTRAINTS

  • I-Tung Yang
    • International conference on construction engineering and project management
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    • 2005.10a
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    • pp.881-885
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    • 2005
  • Scheduling repetitive projects under limitations on the amounts of available resources (labor and equipment) has been an active subject because of its practical relevance. Traditionally, the limitation is specified as a deterministic (fixed) number, such as 1000 labor-hours. The limitation, however, is often exposed to uncertainty and variability, especially when the project is lengthy. This paper presents a stochastic optimization model to treat the situations where the limitations of resources are expressed as probability functions in lieu of deterministic numbers. The proposed model transfers each deterministic resource constraint into a corresponding stochastic one and then solves the problem by the use of a chance-constrained programming technique. The solution is validated by comparison with simulation results to show that it can satisfy the resource constraints with a probability beyond the desired confidence level.

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Time-Optimal Multistage Controllers for Nonlinear Continuous Processes (비선형 연속계를 위한 다단계 시간최적 제어기)

  • Yoon, Joong sun
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.6
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    • pp.128-136
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    • 1995
  • The problem addressed in this paper is that of the on-line computational burden of time-optimal control laws for quick, strongly nonlinear systems like revolute robots. It will be demonstrated that a large amount of off-line computation can be substituted for most of the on-line burden in cases of time optimization with constrained inputs if differential point-to- point specifications can be relaxed to cell-to-cell transitions. These cells result from a coarse discretization of likely swaths of state space into a set of nonuniform, contiguous volumes of relatively simple shapes. The cell boundaries approximate stream surfaces of the phase fluid and surfaces of equal transit times. Once the cells have been designed, the bang- bang schedules for the inputs are determined for all likely starting cells and terminating cells. The scheduling process is completed by treating all cells into which the trajectories might unex- pectedly stray as additional starting cells. Then an efficient-to-compute control law can be based on the resulting table of optimal strategies.

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Simulation Optimization Methods with Application to Machining Process (시뮬레이션 최적화 기법과 절삭공정에의 응용)

  • 양병희
    • Journal of the Korea Society for Simulation
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    • v.3 no.2
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    • pp.57-67
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    • 1994
  • For many practical and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computer simulation is one of the most effective means of studying such complex systems. In this paper, with discussion of simulation optimization techniques, a case study in machining process for application of simulation optimization is presented. Most of optimization techniques can be classified as single-or multiple-response techniques. The optimization of single-response category, these strategies are gradient based search methods, stochastic approximate method, response surface method, and heuristic search methods. In the multiple-response category, there are basically five distinct strategies for treating the responses and finding the optimum solution. These strategies are graphical method, direct search method, constrained optimization, unconstrained optimization, and goal programming methods. The choice of the procedure to employ in simulation optimization depends on the analyst and the problem to be solved.

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A Comparison of Optimization Algorithms: An Assessment of Hydrodynamic Coefficients

  • Kim, Daewon
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.24 no.3
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    • pp.295-301
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    • 2018
  • This study compares optimization algorithms for efficient estimations of ship's hydrodynamic coefficients. Two constrained algorithms, the interior point and the sequential quadratic programming, are compared for the estimation. Mathematical optimization is designed to get optimal hydrodynamic coefficients for modelling a ship, and benchmark data are collected from sea trials of a training ship. A calibration for environmental influence and a sensitivity analysis for efficiency are carried out prior to implementing the optimization. The optimization is composed of three steps considering correlation between coefficients and manoeuvre characteristics. Manoeuvre characteristics of simulation results for both sets of optimized coefficients are close to each other, and they are also fit to the benchmark data. However, this similarity interferes with the comparison, and it is supposed that optimization conditions, such as designed variables and constraints, are not sufficient to compare them strictly. An enhanced optimization with additional sea trial measurement data should be carried out in future studies.

Internet Shopping Optimization Problem With Delivery Constraints

  • Chung, Ji-Bok
    • Journal of Distribution Science
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    • v.15 no.2
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    • pp.15-20
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    • 2017
  • Purpose - This paper aims to suggest a delivery constrained internet shopping optimization problem (DISOP) which must be solved for online recommendation system to provide a customized service considering cost and delivery conditions at the same time. Research design, data, and methodology - To solve a (DISOP), we propose a multi-objective formulation and a solution approach. By using a commercial optimization software (LINDO), a (DISOP) can be solved iteratively and a pareto optimal set can be calculated for real-sized problem. Results - We propose a new research problem which is different with internet shopping optimization problem since our problem considers not only the purchasing cost but also delivery conditions at the same time. Furthermore, we suggest a multi-objective mathematical formulation for our research problem and provide a solution approach to get a pareto optimal set by using numerical example. Conclusions - This paper proposes a multi-objective optimization problem to solve internet shopping optimization problem with delivery constraint and a solution approach to get a pareto optimal set. The results of research will contribute to develop a customized comparison and recommendation system to help more easy and smart online shopping service.