共查询到20条相似文献,搜索用时 31 毫秒
1.
Masatoshi Sakawa Hideki Katagiri 《Central European Journal of Operations Research》2012,20(1):101-117
This paper considers Stackelberg solutions for two-level linear programming problems under fuzzy random environments. To deal
with the formulated fuzzy random two-level linear programming problem, an α-stochastic two-level linear programming problem is defined through the introduction of α-level sets of fuzzy random variables. Taking into account vagueness of judgments of decision makers, fuzzy goals are introduced
and the α-stochastic two-level linear programming problem is transformed into the problem to maximize the satisfaction degree for each
fuzzy goal. Through fractile criterion optimization in stochastic programming, the transformed stochastic two-level programming
problem can be reduced to a deterministic two-level programming problem. An extended concept of Stackelberg solution is introduced
and a numerical example is provided to illustrate the proposed method. 相似文献
2.
This article considers the bilevel linear programming problem with interval coefficients in both objective functions. We propose a cutting plane method to solve such a problem. In order to obtain the best and worst optimal solutions, two types of cutting plane methods are developed based on the fact that the best and worst optimal solutions of this kind of problem occur at extreme points of its constraint region. The main idea of the proposed methods is to solve a sequence of linear programming problems with cutting planes that are successively introduced until the best and worst optimal solutions are found. Finally, we extend the two algorithms proposed to compute the best and worst optimal solutions of the general bilevel linear programming problem with interval coefficients in the objective functions as well as in the constraints. 相似文献
3.
讨论了一类系数为梯形模糊数的两层线性规划问题,首先是利用模糊结构元理论将梯形模糊数去模糊化,将其转化成常规的两层线性问题,并验证其去模糊化后的常规的两层线性规划的最优解与系数为梯形模糊数的两层线性规划问题的最优解一致,并给出具体的算法,数例进行验证. 相似文献
4.
Ghatee and Hashemi [M. Ghatee, S.M. Hashemi, Ranking function-based solutions of fully fuzzified minimal cost flow problem, Inform. Sci. 177 (2007) 4271–4294] transformed the fuzzy linear programming formulation of fully fuzzy minimal cost flow (FFMCF) problems into crisp linear programming formulation and used it to find the fuzzy optimal solution of balanced FFMCF problems. In this paper, it is pointed out that the method for transforming the fuzzy linear programming formulation into crisp linear programming formulation, used by Ghatee and Hashemi, is not appropriate and a new method is proposed to find the fuzzy optimal solution of multi-objective FFMCF problems. The proposed method can also be used to find the fuzzy optimal solution of single-objective FFMCF problems. To show the application of proposed method in real life problems an existing real life FFMCF problem is solved. 相似文献
5.
Mingzhi Chen Sheng-Guo Wang Paul P. Wang Xiaoxiang Ye 《Fuzzy Optimization and Decision Making》2016,15(2):155-175
In this paper, we have introduced a new approach to solve a class of interval linear programming (ILP) problems. Firstly, the novel concept of an interval ordering relation is further developed to make desired solution feasible. Secondly, according to the 3\(\upsigma \) law of normal distribution, a new equivalent transformation for constraints with the interval-valued coefficients of ILP is justified. Accordingly, the uncertainty stemmed from interval number could be replaced by the uncertainty of random variables. Consequently, the classical methodology of stochastic linear programming, a chance constrained programming model based on normal distribution is designed to work out the equivalent form of the original problem. This is because it allows us to carry out the optimization operation with a certain calibrated probability. A typical numerical example is given to illustrate how to apply equivalent transformation in order to realize ILP. Finally, we conclude this paper by elaborated comparisons among our method and selected existing solutions to advance our confidence of our research results as to their correctness and effectiveness. 相似文献
6.
研究了特殊的二层极大极小随机规划逼近收敛问题. 首先将下层初始随机规划最优解集拓展到非单点集情形, 且可行集正则的条件下, 讨论了下层随机规划逼近问题最优解集关于上层决策变量参数的上半收敛性和最优值函数的连续性. 然后把下层随机规划的epsilon-最优解向量函数反馈到上层随机规划的目标函数中, 得到了上层随机规划逼近问题的最优解集关于最小信息概率度量收敛的上半收敛性和最优值的连续性. 相似文献
7.
8.
一类随机多目标二次线性规划模型的交互式算法 总被引:2,自引:0,他引:2
针对线性约束条件下带有一个二次目标函数和多个线性目标函数的随机多目标决策问题,借助参考方向法和权重法对该决策问题的期望值模型进行标量化,获得了关于期望值模型的(恰当/弱)有效解的充要条件,引入Achievement函数建立了一类随机多目标二次线性规划模型的交互式计算方法. 相似文献
9.
10.
双层规划在经济、交通、生态、工程等领域有着广泛而重要的应用.目前对双层规划的研究主要是基于强双层规划和弱双层规划.然而,针对弱双层规划的求解方法却鲜有研究.研究求解弱线性双层规划问题的一种全局优化方法,首先给出弱线性双层规划问题与其松弛问题在最优解上的关系,然后利用线性规划的对偶理论和罚函数方法,讨论该松弛问题和它的罚问题之间的关系.进一步设计了一种求解弱线性双层规划问题的全局优化方法,该方法的优势在于它仅仅需要求解若干个线性规划问题就可以获得原问题的全局最优解.最后,用一个简单算例说明了所提出的方法是可行的. 相似文献
11.
We consider fuzzy stochastic programming problems with a crisp objective function and linear constraints whose coefficients are fuzzy random variables, in particular of type L-R. To solve this type of problems, we formulate deterministic counterparts of chance-constrained programming with fuzzy stochastic coefficients, by combining constraints on probability of satisfying constraints, as well as their possibility and necessity. We discuss the possible indices for comparing fuzzy quantities by putting together interval orders and statistical preference. We study the convexity of the set of feasible solutions under various assumptions. We also consider the case where fuzzy intervals are viewed as consonant random intervals. The particular cases of type L-R fuzzy Gaussian and discrete random variables are detailed. 相似文献
12.
Vyacheslav V. Kalashnikov Gerardo A. Pérez-Valdés Asgeir Tomasgard Nataliya I. Kalashnykova 《European Journal of Operational Research》2010
A stochastic formulation of the natural gas cash-out problem is given in a form of a bilevel multi-stage stochastic programming model with recourse. After reducing the original formulation to a bilevel linear problem, a stochastic scenario tree is defined by its node events, and time series forecasting is used to produce stochastic values for data of natural gas price and demand. Numerical experiments were run to compare the stochastic solution with the perfect information solution and the expected value solutions. 相似文献
13.
This paper considers several probability maximization models for multi-scenario portfolio selection problems in the case that
future returns in possible scenarios are multi-dimensional random variables. In order to consider occurrence probabilities
and decision makers’ predictions with respect to all scenarios, a portfolio selection problem setting a weight with flexibility
to each scenario is proposed. Furthermore, by introducing aspiration levels to occurrence probabilities or future target profit
and maximizing the minimum aspiration level, a robust portfolio selection problem is considered. Since these problems are
formulated as stochastic programming problems due to the inclusion of random variables, they are transformed into deterministic
equivalent problems introducing chance constraints based on the stochastic programming approach. Then, using a relation between
the variance and absolute deviation of random variables, our proposed models are transformed into linear programming problems
and efficient solution methods are developed to obtain the global optimal solution. Furthermore, a numerical example of a
portfolio selection problem is provided to compare our proposed models with the basic model. 相似文献
14.
This paper considers a new optimal location problem, called defensive location problem (DLP). In the DLPs, a decision maker locates defensive facilities in order to prevent her/his enemies from reaching an important site, called a core; for example, “a government of a country locates self-defense bases in order to prevent her/his aggressors from reaching the capital of the country.” It is assumed that the region where the decision maker locates her/his defensive facilities is represented as a network and the core is a vertex in the network, and that the facility locater and her/his enemy are an upper and a lower level of decision maker, respectively. Then the DLPs are formulated as bilevel 0-1 programming problems to find Stackelberg solutions. In order to solve the DLPs efficiently, a solving algorithm for the DLPs based upon tabu search methods is proposed. The efficiency of the proposed solving methods is shown by applying to examples of the DLPs. Moreover, the DLPs are extended to multi-objective DLPs that the decision maker needs to defend several cores simultaneously. Such DLPs are formulated as multi-objective programming problems. In order to find a satisfying solution of the decision maker for the multi-objective DLP, an interactive fuzzy satisfying method is proposed, and the results of applying the method to examples of the multi-objective DLPs are shown. 相似文献
15.
《Operations Research Letters》1987,6(1):53-59
This note outlinestwo test which can be applied, under certain conditions, to solutions to linear multi-objective programming problems. The first test can be used to determine whether a given basic solution to the problem is optimal. The second test can be used to determine whether a given non-basic solution to the problem is optimal in a certain face of the set of feasible solutions of the problem. 相似文献
16.
Bilevel programming approach applied to the flow shop scheduling problem under fuzziness 总被引:1,自引:0,他引:1
Samir A. Abass 《Computational Management Science》2005,2(4):279-293
This paper presents a fuzzy bilevel programming approach to solve the flow shop scheduling problem. The problem considered
here differs from the standard form in that operators are assigned to the machines and imposing a hierarchy of two decision
makers with fuzzy processing times. The shop owner considered higher level and assigns the jobs to the machines in order to
minimize the flow time while the customer is the lower level and decides on a job schedule in order to minimize the makespan.
In this paper, we use the concepts of tolerance membership function at each level to define a fuzzy decision model for generating
optimal (satisfactory) solution for bilevel flow shop scheduling problem. A solution algorithm for solving this problem is
given.
Mathematics Subject Classification:
90C70, 90B36, 90C99 相似文献
17.
From a perspective of non-linear bilevel multi-objective decision-making problem (BMDMP) of the leader-follower Stackelberg game, this paper presents a two-person bilevel multi-objective decision-making model and an interactive algorithm for solving the problem. The algorithm simplifies a BMDMP by transforming it into separate multi-objective decision-making problems at the upper- and lower-levels, thereby avoiding the difficulty associated with non-convex mathematical programming to arrive at an optimal solution. In addition, the authors put forward the satisfactoriness concept as the upper level decision maker's preference. The algorithm facilitates the interactive nature of bilevel multi-objective decision making for non-inferior solutions. Thus, the algorithm provides a way to solve BMDMP. 相似文献
18.
This paper proposes a decomposition method for hierarchical generation of α-Pareto optimal solutions in large-scale multi-objective non-linear programming (MONLP) problems with fuzzy parameters in the objective functions and in the constraints (FMONLP). These fuzzy parameters are characterized by fuzzy numbers. For such problems, the concept of α-Pareto optimality introduced by extending the ordinary Pareto optimality based on the α-level sets of fuzzy numbers. The decomposition method is based on the principle of decompose the original problem into interdependent sub-problems. In this method, the global multi-objective non-linear problem is decomposed into smaller multi-objective sub-problems. The smaller sub-problems, which obtained solved separately by using the weighting method and through an operative procedure. All these solution are coordinates in such a way that an optimal solution for the global problem achieved. In addition, an interactive fuzzy decision-making algorithm for hierarchical generation of α-Pareto optimal solution through the decomposition method is developed. Finally, two numerical examples given to illustrate the results developed in this paper. 相似文献
19.
H.-J. Zimmermann 《Fuzzy Sets and Systems》1978,1(1):45-55
In the recent past numerous models and methods have been suggested to solve the vectormaximum problem. Most of these approaches center their attention on linear programming problems with several objective functions. Apart from these approaches the theory of fuzzy sets has been employed to formulate and solve fuzzy linear programming problems. This paper presents the application of fuzzy linear programming approaches to the linear vectormaximum problem. It shows that solutions obtained by fuzzy linear programming are always efficient solutions. It also shows the consequences of using different ways of combining individual objective functions in order to determine an “optimal” compromise solution. 相似文献
20.
本文基于模糊结构元方法建立并讨论了一类含有直觉模糊弹性约束的广义模糊变量线性 规划问题。首先,简单介绍了结构元方法并对结构元加权排序中权函数表征决策者风险态度进行了深入分析。然后,通过选取风险中立型决策态度来定义序关系并拓展Verdegay模糊线性规划方法,将新型模糊变量线性规划问题转化为两个含一般模糊弹性约束的模糊变量线性规划模型,给出了此类规划最优直觉模糊解的求法。最后,通过数值算例进一步说明该方法的有效性。 相似文献