This paper developed a new sensitivity analysis in the Efficient Decision-Making Units (DMUs) for Data Envelopment Analysis (DEA) model when the data uncertainty occurred locally. We consider the stability of an effic...
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This paper developed a new sensitivity analysis in the Efficient Decision-Making Units (DMUs) for Data Envelopment Analysis (DEA) model when the data uncertainty occurred locally. We consider the stability of an efficient DMU by deteriorating a class of DMUs simultaneously in the same directions to keep the test DMU remains on the efficient frontier. The approach generalizes the usual DEA sensitivity analysis in which the data variations are considered either on the single test DMU or on the allover DMUs. This enables the decision maker to take suitable actions that meet the possible local variations.
This paper studies the single machine scheduling problem for the objective of minimizing the expected number of tardy jobs. Jobs have normally distributed processing times and a common deterministic due date. We devel...
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This paper studies the single machine scheduling problem for the objective of minimizing the expected number of tardy jobs. Jobs have normally distributed processing times and a common deterministic due date. We develop new approaches for this problem that generate near optimal solutions. The original stochastic problem is transformed into a non-linear integer programming model and its relaxations. Computational study validates their effectiveness by comparison with optimal solutions. (c) 2005 Published by Elsevier Ltd.
Hypothetical reasoning is an important framework for knowledge-based systems, however, its inference time grows exponentially with respect to problem size. In this paper, we present an understandable efficient method ...
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Hypothetical reasoning is an important framework for knowledge-based systems, however, its inference time grows exponentially with respect to problem size. In this paper, we present an understandable efficient method called slide-down and lift-up (SL) method which uses a linearprogramming technique for determining an initial search point and a non-linear programming technique for efficiently finding a near-optimal 0-1 solution. To escape from trapping into local optima, we have developed a new local handler, which systematically fixes a variable to a locally consistent value. Since the behavior of the SL method is illustrated visually, the simple inference mechanism of the method can be easily understood. (C) 2002 Elsevier Science B.V. All rights reserved.
Over the past three decades Evolutionary Algorithms have emerged as a powerful mechanism for finding solutions to large and complex problems. A promising new evolutionary algorithm known as Differential Evolution (DE)...
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Over the past three decades Evolutionary Algorithms have emerged as a powerful mechanism for finding solutions to large and complex problems. A promising new evolutionary algorithm known as Differential Evolution (DE) was recently introduced and has garnered significant attention in the research literature. This paper introduces a modification to DE that enhances its rate of convergence without compromising solution quality. DE was recently shown to outperform several well-known stochastic optimization methods on an extensive set of test problems. Our Modified Differential Evolution (MDE) algorithm utilizes selection pressure to develop offspring that are more fit to survive than those generated from purely random operators. We demonstrate that MDE requires less computational effort to locate global optimal solutions to well-known test problems in the continuous domain. (c) 2004 Elsevier Ltd. All rights reserved.
An important concept proposed in the early stage of robot path planning field is the shrinking of a robot to a point and meanwhile the expanding of obstacles in the workspace as a set of new obstacles. The resulting g...
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An important concept proposed in the early stage of robot path planning field is the shrinking of a robot to a point and meanwhile the expanding of obstacles in the workspace as a set of new obstacles. The resulting grown obstacles are called the Configuration Space (Cspace) obstacles. The find-path problem is then transformed into that of finding a collision-free path for a point robot among the Cspace obstacles. However, the research experiences have shown that the Cspace transformation is very hard when the following situations occur: 1) both the robot and obstacles are not polygons, and 2) the robot is allowed to rotate. This situation gets even worse when the robot and obstacles are three dimensional (3D) objects with various shapes. For this reason, direct path planning approaches without the Cspace transformation is quite useful and expected. Motivated by the practical requirements of robot path planning, a generalized constrained optimization problem (GCOP) with not only logic AND but also logic OR relationships was proposed and a mathematical solution developed previously. This paper inherits the fundamental ideas of inequality and optimization techniques from the previous work, converts the obstacle avoidance problem into a semi-infinite constrained optimization problem with the help of the mathematical transformation, and proposes a direct path planning approach without Cspace calculation, which is quite different from traditional methods. To show its merits, simulation results in 3D space have been presented.
It is well known that among the current methods for unconstrained optimization problems the quasi-Newton methods with global strategy may be the most efficient methods, which have local superlinear convergence. Howeve...
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It is well known that among the current methods for unconstrained optimization problems the quasi-Newton methods with global strategy may be the most efficient methods, which have local superlinear convergence. However, when the iterative point is far away from the solution of the problem, quasi-Newton method may proceed slowly for the general unconstrained optimization problems. In this article an adaptive conic trust-region method for unconstrained optimization is presented. Not only the gradient information but also the values of the objective function are used to construct the local model at the current iterative point. Moreover, we define a concept of super steepest descent direction and embed its information into the local model. The amount of computation in each iteration of this adaptive algorithm is the same as that of the standard quasi-Newton method with trust region. Some numerical results show that the modified method requires fewer iterations than the standard methods to reach the solution of the optimization problem. Global and local convergence of the method is also analyzed.
The paper refers to previous works developed by the authors, dealing with the possibility of applying duality theorems to non-linear programs coming out from limit analysis (LA) of structures made by not resisting ten...
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The paper refers to previous works developed by the authors, dealing with the possibility of applying duality theorems to non-linear programs coming out from limit analysis (LA) of structures made by not resisting tension (NRT) or no-tension material. Under such perspective, after setting up the static or kinematic LA problem for NRT structures, the main task, for duality theorems to be applicable, is to demonstrate some convexity-related properties of the involved functions and domains. This feature, which is of basic importance for the whole procedure, is not trivial since all of the required conditions are to be accurately checked by analytical developments. Application of duality is finally demonstrated to give a complete and clear interpretation from a physical point of view about relationships relevant to LA approaches. (C) 2005 Elsevier Ltd. All rights reserved.
This paper discusses the application of the softened truss and strut and tie models on short beams. The softened truss model originally proposed by Hsu is based on three fundamental principles of mechanics of material...
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This paper discusses the application of the softened truss and strut and tie models on short beams. The softened truss model originally proposed by Hsu is based on three fundamental principles of mechanics of materials, i.e., stress equilibrium, strain compatibility, and constitutive laws of materials. The model has two important characteristics. The first is the non-linear association of stress and strain. The second is the softening of concrete in compression due to tensile strains in the perpendicular direction. For short beams, one of the most important factors influencing behaviour is the effective transverse compression, which is dependent on the shear-span-to-depth (a/d) ratio. In this study, the softened truss model is revised so that the model gives more accurate predictions of the shear strength of short beams. The revised softened truss model (RSOTM) has three differences from the original model. In the RSOTM, it is shown that the effective transverse compression is not only dependent on the a/d ratio but also on the reinforcement ratio in the longitudinal direction as well as the size of the specimen. Second, it is shown that the softening phenomenon in short beams is more severe than that assumed in the original model. The third difference is that the effective transverse compression will be zero when a/d ratio exceeds 1.5. The ROSTM is compared with ACI318-2002, which recommends that short and deep beams should be designed by strut and tie models. ACI318-2002 and the final draft of Eurocode 2 do not provide specific guidance on suitable strut and tie models for different cases. In this study on short beams, a strut and tie model which consists of three mechanisms is recommended: a direct strut mechanism to account for the contribution of concrete and two truss mechanisms to account for the contributions of the horizontal and vertical shear reinforcements to the shear strength. It is imperative that ACI318-2002 and the final draft of Eurocode 2 should b
This paper presents an optimal operation study of the power system via sensitivity analysis. This study is based on perturbation of optimum theorem, which works with a Lagrangian function associated with the perturbed...
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This paper presents an optimal operation study of the power system via sensitivity analysis. This study is based on perturbation of optimum theorem, which works with a Lagrangian function associated with the perturbed problem. Starting from an optimal operating point obtained by solution of an optimal power flow problem, the new optimal operating point is calculated directly satisfying the constraints and optimising the objective function after making a small perturbation in the loads. Test results are presented to demonstrate the efficiency of the approach. (c) 2005 Elsevier B.V. All rights reserved.
作者:
Patra, C.Basudhar, P.NIT
Civil Engn Rourkela 769008 India IIT
Civil Engn Kanpur 208016 Uttar Pradesh India
In this paper, a generalized method of computer based optimum design of soil-nailed slopes is reported. A limit equilibrium formulation satisfying overall and internal equilibrium and considering the effect of tensile...
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In this paper, a generalized method of computer based optimum design of soil-nailed slopes is reported. A limit equilibrium formulation satisfying overall and internal equilibrium and considering the effect of tensile resistance of the reinforcement has been used in computing the stability of nailed slopes. The quantity of steel requirement for raising the factor of safety to a desired value is estimated. The location, size (length and diameter) and orientation of the nails and the location and shape of the critical shear surface have been treated as variables. The solutions have been isolated by formulating the problem as one of non-linear programming. The applicability of the developed method has been verified by comparing the predicted failure surfaces with those observed in model tests as well as in the field and also reported theoretical results.
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