A method for optimizing the variety of a modular products, manufactured in a Reconfigurable Manufacturing System, is proposed. The optimization is achieved through appropriately selecting the subsets of module instanc...
详细信息
A method for optimizing the variety of a modular products, manufactured in a Reconfigurable Manufacturing System, is proposed. The optimization is achieved through appropriately selecting the subsets of module instances from given sets. The problem is formulated as an integer nonlinear programming problem to find a trade-off between the quality loss due to modularity and the cost of reconfiguration for given sets of customer requirements. The proposed formulation is general in the sense that products can have any number of modules. The formulation is an extension to the available formulation that was developed for products with only two modules. Moreover, the current work addresses the effect of different order priorities, customer importance, and demands. The proposed method has been applied to a modular assembly problem and found to be efficient in determining optimum subsets of module instances.
In this paper we consider the purchasing decisions facing a buying firm which receives incrementally discounted price schedules for a group of items in the presence of constraints such as budgets and space limitations...
详细信息
In this paper we consider the purchasing decisions facing a buying firm which receives incrementally discounted price schedules for a group of items in the presence of constraints such as budgets and space limitations. The constraints take the form of upper bounds on positively weighted linear combinations of order size, dollar volume, unit price and order frequency. We adapt the solution procedures from an earlier paper [Naval Res. Logis. 40 (2) (1993) 255] to treat this case. The results show that simultaneous order quantities for multiple items, offered with separate incremental discounts and subject to joint resource constraints, can be calculated efficiently using a combination of Lagrangean relaxation and, as needed, partial enumeration. This problem proved to be no more and no less tractable than its counterpart with all units discounts. (C) 2002 Elsevier Science B.V. All rights reserved.
Mathematical programs with equilibrium constraints (MPECs) form a relatively new and interesting subclass of nonlinear programming problems. In this paper we propose a novel method of solving MPECs by appropriate refo...
详细信息
Mathematical programs with equilibrium constraints (MPECs) form a relatively new and interesting subclass of nonlinear programming problems. In this paper we propose a novel method of solving MPECs by appropriate reformulation of the equilibrium conditions. The reformulation can be easily incorporated in a certain class of interior point algorithms for nonlinear optimization. The algorithm used in the study follows a primal-dual interior point approach and shows encouraging results on a test suite of MPECs. The algorithm is also able to perform optimization of distillation columns with phase changes and tray optimization using only continuous variables. We also consider a number of topics to improve performance of the algorithm and to identify classes of process engineering problems that can be handled as MPECs. (C) 2003 Elsevier Science Ltd. All rights reserved.
In this paper, we propose a method to solve the distributed constrained state-estimation problem and discuss the associated implementation. This method includes a successive quadratic programming process and a paralle...
详细信息
In this paper, we propose a method to solve the distributed constrained state-estimation problem and discuss the associated implementation. This method includes a successive quadratic programming process and a parallel dual-type method possessing decomposition effects. With the decomposition, our method achieves a dramatic speed-up ratio compared with the commercial IMSL subroutines in solving CWLS problems. (C) 2003 Elsevier Science B.V. All rights reserved.
This work presents two new error estimation approaches for the BEM applied to 2D potential problems. The first approach involves a local error estimator based on a gradient recovery procedure in which the error functi...
详细信息
This work presents two new error estimation approaches for the BEM applied to 2D potential problems. The first approach involves a local error estimator based on a gradient recovery procedure in which the error function is generated from differences between smoothed and non-smoothed rates of change of boundary variables in the local tangential direction. The second approach involves the external problem formulation and gives both local and global measures of error, depending on a choice of the external evaluation point. These approaches are post-processing procedures. Both estimators show consistency with mesh refinement and give similar qualitative results. The error estimator using the gradient recovery approach is more general, as this formulation does not rely on an 'optimal' choice of an external parameter. This work presents also the use of a local error estimator in an adaptive mesh refinement procedure. This r-refinement approach is based on the minimization of the standard deviation of the local error estimate. A non-linear programming procedure using a feasible-point method is employed using Lagrange multipliers and a set of active constraints. The optimization procedure produces finer meshes close to a singularity and results that are consistent with the problem physics. Copyright (C) 2002 John Wiley Sons, Ltd.
Based on the lower bound theorem of limit analysis, a solution procedure for limit analysis of three_dimensional elastoplastic structures was established using conventional boundary element method (BEM). The elastic s...
详细信息
Based on the lower bound theorem of limit analysis, a solution procedure for limit analysis of three_dimensional elastoplastic structures was established using conventional boundary element method (BEM). The elastic stress field for lower bound limit analysis was computed directly by three_dimensional boundary element method (3_D BEM). The self_equilibrium stress field was constructed by the linear combination of several self_equilibrium “basis vectors” which can be computed by elastic_plastic incremental iteration of 3_D BEM analysis. The lower bound limit analysis problem was finally reduced to a series of nonlinear programming sub_problems with relatively few optimal variables. The complex method was used to solve the nonlinear programming sub_problems. The numerical results show that the present solution procedure has good accuracy and high efficiency.
Canonical analysis is a common method for exploring and exploiting fitted quadratic response surfaces. Much attention in canonical analysis is given to identifying ridge behavior in these surfaces in order to achieve ...
详细信息
Canonical analysis is a common method for exploring and exploiting fitted quadratic response surfaces. Much attention in canonical analysis is given to identifying ridge behavior in these surfaces in order to achieve optimal response at minimum cost. However, little attention has been given to classifying the identified ridge as a stationary ridge or a rising ridge. Knowing whether a ridge is stationary or rising is critical for making decisions about how to continue the response surface exploration or for setting process parameters. This article presents two methods that allow for identification, classification and confirmation of ridge behavior. The first method is based on linear regression and though easily implemented, can be imprecise. The second method is more precise and is based on a new parameterization of the canonical form. It uses nonlinear regression techniques that are becoming increasingly accessible through software packages.
Regression is a very powerful methodology for forecasting, which is considered as an essential component of successful OR applications. In this paper an idea stemmed from the classical least squares is proposed to han...
详细信息
Regression is a very powerful methodology for forecasting, which is considered as an essential component of successful OR applications. In this paper an idea stemmed from the classical least squares is proposed to handle fuzzy observations in regression analysis. Based on the extension principle, the membership function of the sum of squared errors is constructed. The fuzzy sum of squared errors is a function of the regression coefficients to be determined, which can be minimized via a nonlinear program formulated under the structure of the Chen-Klein method for ranking fuzzy numbers. To illustrate how the proposed method is applied, three cases, one crisp input-fuzzy output, one fuzzy input-fuzzy output, and one non-triangular fuzzy observations, are exemplified. The results show that the least-squares method of this paper is able to determine the regression coefficients with better explanatory power. Most important, it works for all types of fuzzy observations, not restricted to the triangular one. (C) 2002 Elsevier Science B.V. All rights reserved.
Direct search methods are best known as unconstrained optimization techniques that do not explicitly use derivatives. Direct search methods were formally proposed and widely applied in the 1960s but fell out of favor ...
详细信息
Direct search methods are best known as unconstrained optimization techniques that do not explicitly use derivatives. Direct search methods were formally proposed and widely applied in the 1960s but fell out of favor with the mathematical optimization community by the early 1970s because they lacked coherent mathematical analysis. Nonetheless, users remained loyal to these methods, most of which were easy to program, some of which were reliable. In the past fifteen years, these methods have seen a revival due, in part, to the appearance of mathematical analysis, as well as to interest in parallel and distributed computing. This review begins by briefly summarizing the history of direct search methods and considering the special properties of problems for which they are well suited. Our focus then turns to a broad class of methods for which we provide a unifying framework that lends itself to a variety of convergence results. The underlying principles allow generalization to handle bound constraints and linear constraints. We also discuss extensions to problems with nonlinear constraints.
The problem of determining elastic buckling strengths for unbraced steel frames under variable loading is investigated in this paper. Whereas the pattern of applied loads is specified prior to stability analysis of a ...
详细信息
The problem of determining elastic buckling strengths for unbraced steel frames under variable loading is investigated in this paper. Whereas the pattern of applied loads is specified prior to stability analysis of a frame under proportional loading, load patterns are not predefined in variable loading. The conventional methods for evaluating the stability strength of unbraced frames under proportional loading are not applicable for variable loading, since the load pattern is unknown. Taking into account the concept of storey-based buckling, the problem of frame stability under variable loading is presented as a pair of minimization and maximization problems subject to stability constraints, which are solved by a nonlinear programming (NLP) method. The proposed variable loading approach takes into account the variability of applied loads during the life span of the structure, and as such, provides accurate evaluation of elastic frame-buckling strengths.
暂无评论