In this paper a general strategy for process design using nonlinear goal programming is developed and applied to machining operations. The developed strategy allows different priority levels for each objective. The re...
详细信息
In this paper a general strategy for process design using nonlinear goal programming is developed and applied to machining operations. The developed strategy allows different priority levels for each objective. The resulting design and optimization problem can be solved using unconstrained nonlinear techniques with no need for linearization. Evaluation of the developed strategy was conducted using single pass machining operations. The study proved the effectiveness of the strategy in selecting the optimum process conditions under different production priorities. The developed strategy is also compared with a strategy based on a fuzzy nonlinear programming model. The fuzzy-based solution can be considered as the fuzzy alternative or the approximation of the multiple objective solution.
Several filled functions were reported to seek the global minimum of multimodal functions of multiple variables. This Paper proposes an alternative formulation that may reduce the negative definite effect of the Hessi...
详细信息
Several filled functions were reported to seek the global minimum of multimodal functions of multiple variables. This Paper proposes an alternative formulation that may reduce the negative definite effect of the Hessian of a filled function proposed before. Furthermore, a class of mitigators is defined and applied to improve the computational characteristics of filled functions. Results of numerical experiments on typical testing functions are also reported. (C) 2002 Elsevier Science Inc. All rights reserved.
Cross-border passengers from Hong Kong to Shenzhen by the east Kowloon-Canton Railway (KCR) through the Lo Wu customs exceed nearly 200 thousand on a special day such as a day during the Chinese Spring Festival. Such ...
详细信息
Cross-border passengers from Hong Kong to Shenzhen by the east Kowloon-Canton Railway (KCR) through the Lo Wu customs exceed nearly 200 thousand on a special day such as a day during the Chinese Spring Festival. Such heavy passenger demand often exceeds the processing and holding capacity of the Lo Wu customs for many hours a day. Thus, passengers must be metered off at all entrance stations along the KCR line through ticket rationing to restrain the number of passengers waiting at Lo Wu within its safe holding capacity. This paper proposes an optimal control strategy and model to deal with this passenger crowding and control problem. Because the maximum passenger checkout rate at Lo Wu is fixed, total passenger waiting time is not affected by the control strategy for given time-dependent arriving rates at each station. An equity-based control strategy is thus proposed to equalize the waiting times of passengers arriving at all stations at the same time. This equity is achieved through optimal allocation of the total quota of tickets to all entrance stations for each train service. The total ticket quota for each train service is determined such that the capacity constraint of the passenger queue at Lo Wu is satisfied. The control problem is formulated as a successive linear programming problem and demonstrated for the KCR system with partially simulated data.
We consider the nonlinear programming problem (sic)-->{min f(x)\g(i)(x)less than or equal tob(i), i-1,...,m} with f positively p-homogeneous and g(i) positively q-homogeneous functions. We show that (sic) admits a ...
详细信息
We consider the nonlinear programming problem (sic)-->{min f(x)\g(i)(x)less than or equal tob(i), i-1,...,m} with f positively p-homogeneous and g(i) positively q-homogeneous functions. We show that (sic) admits a simple min-max formulation (sic) with the inner max-problem being a trivial linear program with a single constraint. This provides a new formulation of the linear programming problem and the linear-quadratic one as well. In particular, under some conditions, a global (nonconvex) optimization problem with quadratic data is shown to be equivalent to a convex minimization problem.
This paper discusses nonlinear optimization techniques in robust control synthesis, with special emphasis on design problems which may be cast as minimizing a linear objective function under linear matrix inequality (...
详细信息
This paper discusses nonlinear optimization techniques in robust control synthesis, with special emphasis on design problems which may be cast as minimizing a linear objective function under linear matrix inequality (LMI) constraints in tandem with nonlinear matrix equality constraints. The latter type of constraints renders the design numerically and algorithmically difficult. We solve the optimization problem via sequential semidefinite programming (SSDP), a technique which expands on sequential quadratic programming (SQP) known in nonlinear optimization. Global and fast local convergence properties of SSDP are similar to those of SQP, and SSDP is conveniently implemented with available semidefinite programming ( SDP) solvers. Using two test examples, we compare SSDP to the augmented Lagrangian method, another classical scheme in nonlinear optimization, and to an approach using concave optimization.
A trajectory optimization technique based upon higher-order collocation is used to solve optimal, low-thrust, Earth-orbit transfer problems. The optimal control problem solved is defined, and the solution method for s...
详细信息
A trajectory optimization technique based upon higher-order collocation is used to solve optimal, low-thrust, Earth-orbit transfer problems. The optimal control problem solved is defined, and the solution method for solving this problem is described. For several example cases analyzed, a spacecraft is transferred from low Earth orbit to a variety of final mission orbits. A range of thrust accelerations from approximately 1 to 10(-3) g was used. A comparison is made between the optimal transfers found in this work and the transfers found by using analytical blended control methods. Finally, conclusions drawn from this work are discussed.
The stability number alpha(G) for a given graph G is the size of a maximum stable set in G. The Lovasz theta number provides an upper bound on alpha(G) and can be computed in polynomial time as the optimal value of th...
详细信息
The stability number alpha(G) for a given graph G is the size of a maximum stable set in G. The Lovasz theta number provides an upper bound on alpha(G) and can be computed in polynomial time as the optimal value of the Lovasz semidefinite program. In this paper, we show that restricting the matrix variable in the Lovasz semidefinite program to be rank-one and rank-two, respectively, yields a pair of continuous, nonlinear optimization problems each having the global optimal value alpha(G). We propose heuristics for obtaining large stable sets in G based on these new formulations and present computational results indicating the effectiveness of the heuristics.
We examine the sequence of local minimizers of the log-barrier function for a nonlinear program near a solution at which second-order sufficient conditions and the Mangasarian-Fromovitz constraint qualification are sa...
详细信息
We examine the sequence of local minimizers of the log-barrier function for a nonlinear program near a solution at which second-order sufficient conditions and the Mangasarian-Fromovitz constraint qualification are satisfied, but the active constraint gradients are not necessarily linearly independent, When a strict complementarity condition is satisfied, we show uniqueness of the local minimizer of the barrier function in the vicinity of the nonlinear program solution, and we obtain a semiexplicit characterization of this point. When strict complementarity does not hold, we obtain several other interesting characterizations, in particular, an estimate of the distance between the minimizers of the barrier function and the nonlinear program in terms of the barrier parameter, and a result about the direction of approach of the sequence of minimizers of the barrier function to the nonlinear programming solution.
This paper describes the use of a stochastic search procedure based on genetic algorithms for developing near-optimal topologies of load-bearing truss structures. Most existing cases these publications express the tru...
详细信息
This paper describes the use of a stochastic search procedure based on genetic algorithms for developing near-optimal topologies of load-bearing truss structures. Most existing cases these publications express the truss topology as a combination of members. These methods, however, have the disadvantage that the resulting topology may include needless members or those which overlap other members. In addition to these problems, the generated structures are not necessarily structurally stable. A new method, which resolves these problems by expressing the truss topology as a combination of triangles, is proposed in this paper. Details of the proposed methodology are presented as well as the results of numerical examples that clearly show the effectiveness and efficiency of the method.
A solution procedure for lower bound limit analysis is presented making use of the Symmetric Galerkin Boundary Element Method (SGBEM) rather than of finite element method. The self-equilibrium stress fields are expres...
详细信息
A solution procedure for lower bound limit analysis is presented making use of the Symmetric Galerkin Boundary Element Method (SGBEM) rather than of finite element method. The self-equilibrium stress fields are expressed by linear combination of several basic self-equilibrium stress fields with parameters to be determined. These basic self-equilibrium stress fields are expressed as elastic responses of the body to imposed permanent strains obtained through elastic-plastic incremental analysis. The Complex method is used to solve nonlinear programming and determine the maximal load amplifier. The numerical results show that it is efficient and accurate to solve limit analysis problems by using the SGBEM and the Complex method. (C) 2001 Elsevier Science B.V. All rights reserved.
暂无评论