• 제목/요약/키워드: Programming Right

검색결과 73건 처리시간 0.027초

STABILITY OF EQUIVALENT PROGRAMMING PROBLEMS OF THE MULTIPLE OBJECTIVE LINEAR STOCHASTIC PROGRAMMING PROBLEMS

  • Cho, Gyeong-Mi
    • 대한수학회지
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    • 제35권2호
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    • pp.259-268
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    • 1998
  • In this paper the stochastic multiple objective programming problems where the right-hand-side of the constraints is stochastic are considered. We define the equivalent scalar-valued problem and study the stability of the equivalent scalar-valued problem with respect to the weight parameters and probability mesures under reasonable assumptions.

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0 - 1 목표계획모형의 재구조화에 관한 연구-기회제약계획법(CCP)과 계층화 분석과정(AHP)의 결합 가능성을 중심으로- (A Study of the Reformulation of 0-1 Goal Programming)

  • 이영찬;민재형
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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    • pp.525-529
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    • 1996
  • Decision environments involve a high degree of uncertainty as well as multiple, conflicting goals. Although traditional goal programming offers a means of considering multiple, conflicting goals and arrives at a satisficing solution in a deterministic manner, its major drawback is that decision makers often specify aspiration level of each goal as a single number. To overcome the problem of setting aspiration levels, chance constrained programming can be incorporated into goal programming formulation so that sampling information can be utilized to describe uncertainty distribution. Another drawback of goal programming is that it does not provide a systematic approach to set priorities and trade-offs among conflicting goals. To overcome this weekness, the analytic hierarchy process(AHP) is used in the model. Also, most goal programming models in the literature are of a linear form, although some nonlinear models have been presented. Consideration of risk in technological coefficients and right hand sides, however, leads to nonlinear goal programming models, which require a linear approximation to be solved. In this paper, chance constrained reformulation with linear approximation is presented for a 0-1 goal programming problem whose technological coefficients and right hand sides are stochastic. The model is presented with a numerical example for the purpose of demonstration.

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퍼지목표계획(目標計劃) 모형(模型)의 보조문제화(補助問題化) (On Auxiliary Linear Programming Problems for Fuzzy Goal Programming)

  • 박상규
    • 품질경영학회지
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    • 제20권1호
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    • pp.101-106
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    • 1992
  • In this paper fuzzy goal programming problems with fuzzy constraints and fuzzy coefficients in both matrix and right hand side of the constraints set are considered. Because of fuzzy coefficients in both members of each constraint ranking methods for fuzzy numbers are considered. An additive model to solve fuzzy goal programming problems is formulated. The diversity of each methods provides a lot of different models of auxiliary linear programming problems from which fuzzy solutions to the fuzzy goal programming problem can be obtained.

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동적 계획법을 이용한 스테레오 대응 알고리즘 (Stereo Correspondence Algorithm Using Dynamic programming)

  • 이충환;홍석교
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.310-310
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    • 2000
  • The main problem in stereo vision is to find corresponding points in left and right image known as correspondence problem. Once correspondences determined, the depth information of those points are easily computed form the pairs of points in both image. In this paper, dynamic programming considering half-occluded region is used fer solving correspondence problem.

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블록 대각 구조를 지닌 2단계 확률계획법의 분해원리 (A Decomposition Method for Two stage Stochstic Programming with Block Diagonal Structure)

  • 김태호;박순달
    • 한국경영과학회지
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    • 제10권1호
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    • pp.9-13
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    • 1985
  • This paper develops a decomposition method for stochastic programming with a block diagonal structure. Here we assume that the right-hand side random vector of each subproblem is differente each other. We first, transform this problem into a master problem, and subproblems in a similar way to Dantizig-Wolfe's Decomposition Princeple, and then solve this master problem by solving subproblems. When we solve a subproblem, we first transform this subproblem to a Deterministic Equivalent Programming (DEF). The form of DEF depends on the type of the random vector of the subproblem. We found the subproblem with finite discrete random vector can be transformed into alinear programming, that with continuous random vector into a convex quadratic programming, and that with random vector of unknown distribution and known mean and variance into a convex nonlinear programming, but the master problem is always a linear programming.

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확장된 일반상한제약을 갖는 이차원 선형계획 배낭문제 연구 (On a Two Dimensional Linear Programming Knapsack Problem with the Extended GUB Constrain)

  • 원중연
    • 대한산업공학회지
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    • 제27권1호
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    • pp.25-29
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    • 2001
  • We present a two dimensional linear programming knapsack problem with the extended GUB constraint. The presented problem is an extension of the cardinality constrained linear programming knapsack problem. We identify some new properties of the problem and derive a solution algorithm based on the parametric analysis for the knapsack right-hand-side. The solution algorithm has a worst case time complexity of order O($n^2logn$). A numerical example is given.

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Determining the Efficient Solutions for Bicriteria Programming Problems with Random Variables in Both the Objective Functions and the Constraints

  • Bayoumi, B.I.;El-Sawy, A.A.;Baseley, N.L.;Yousef, I.K.;Widyan, A.M.
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제9권1호
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    • pp.99-110
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    • 2005
  • This paper suggests an efficient approach for stochastic bicriteria programming problem (SBCPP) with random variables in both the objective functions and in the right-hand side of the constraints. The suggested approach uses the statistical inference through two different techniques: In one of them, the SBCPP is transformed into an equivalent deterministic bicriteria programming problem (DBCPP), then the nonnegative weighted sum approach will be used to transform the bicriteria programming problem into a single objective programming problem, and the other technique, the nonnegative weighted sum approach is used to transform the SBCPP to an equivalent stochastic single objective programming problem, then apply the same procedure to convert stochastic single objective programming problem into its equivalent deterministic single objective programming problem (DSOPP). In both techniques the resulting problem can be solved as a nonlinear programming problem to get the efficient solutions. Finally, a comparison between the two different techniques is discussed, and illustrated example is given to demonstrate the actual application of these techniques.

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A Fuzzy-Goal Programming Approach For Bilevel Linear Multiple Objective Decision Making Problem

  • Arora, S.R.;Gupta, Ritu
    • Management Science and Financial Engineering
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    • 제13권2호
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    • pp.1-27
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    • 2007
  • This paper presents a fuzzy-goal programming(FGP) approach for Bi-Level Linear Multiple Objective Decision Making(BLL-MODM) problem in a large hierarchical decision making and planning organization. The proposed approach combines the attractive features of both fuzzy set theory and goal programming(GP) for MODM problem. The GP problem has been developed by fixing the weights and aspiration levels for generating pareto-optimal(satisfactory) solution at each level for BLL-MODM problem. The higher level decision maker(HLDM) provides the preferred values of decision vector under his control and bounds of his objective function to direct the lower level decision maker(LLDM) to search for his solution in the right direction. Illustrative numerical example is provided to demonstrate the proposed approach.

An expansion technique for tolerance approach to sensitivity analysis in linear programming

  • Kim, Koonchan;Jo, Young-Soo;Kang, Young-Yug
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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    • pp.549-552
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    • 1996
  • The tolerance approach to the sensitivity analysis in linear programming considers simultaneous and independent variations in the coefficients of the objective funciton or of the right-hand side terms and gives a region in which the coefficients and terms and gives a region in which the coefficients and terms can be changed and still the current optimal basis B for the original problem remains as an optimal basis for the perturbed problem. In this paper we describe a procedure that expands a region S obtained by the tolerance approch into a larger region R, so that more variations in the objective function coefficients or the right-hand side terms are permissible.

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A Geometrical Expansion Technique for Tolerance Approach to Sensitivity Analysis in Linear Programming

  • Kim, Koon Chan;Jo, Young Soo;Kang, Young Yug
    • 한국경영과학회지
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    • 제21권2호
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    • pp.35-47
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    • 1996
  • The tolerance approach to the sensitivity analysis in linear programming considers simultaneous and independent variations in the coefficients of the objective function or of the right-hand side terms and gives a region in which the coefficients and terms can be changed and still keeps the current optimal basis B for the original problem as an optimal basis for the perturbed problem. In this paper we describe a procedure that expands the region S obtained by the tolerance approach into a larger region R, so that more variations in the objective function coefficients or the right-hand side terms are permissible.

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