Results 1  10
of
85
VLSI cell placement techniques
 ACM Computing Surveys
, 1991
"... VLSI cell placement problem is known to be NP complete. A wide repertoire of heuristic algorithms exists in the literature for efficiently arranging the logic cells on a VLSI chip. The objective of this paper is to present a comprehensive survey of the various cell placement techniques, with emphasi ..."
Abstract

Cited by 88 (0 self)
 Add to MetaCart
VLSI cell placement problem is known to be NP complete. A wide repertoire of heuristic algorithms exists in the literature for efficiently arranging the logic cells on a VLSI chip. The objective of this paper is to present a comprehensive survey of the various cell placement techniques, with emphasis on standard ce11and macro
A stochastic programming approach for supply chain network design under uncertainty
, 2003
"... ..."
Decomposition Algorithms for Stochastic Programming on a Computational Grid
 Computational Optimization and Applications
, 2001
"... . We describe algorithms for twostage stochastic linear programming with recourse and their implementation on a grid computing platform. In particular, we examine serial and asynchronous versions of the Lshaped method and a trustregion method. The parallel platform of choice is the dynamic, heter ..."
Abstract

Cited by 58 (7 self)
 Add to MetaCart
(Show Context)
. We describe algorithms for twostage stochastic linear programming with recourse and their implementation on a grid computing platform. In particular, we examine serial and asynchronous versions of the Lshaped method and a trustregion method. The parallel platform of choice is the dynamic, heterogeneous, opportunistic platform provided by the Condor system. The algorithms are of masterworker type (with the workers being used to solve secondstage problems), and the MW runtime support library (which supports masterworker computations) is key to the implementation. Computational results are presented on large sample average approximations of problems from the literature. 1.
Hybrid Benders Decomposition Algorithms in Constraint Logic Programming
 In Procs. of the 7th Intern. Conference on Principles and Practice of Constraint Programming  CP 2001
, 2001
"... Benders Decomposition is a form of hybridisation that allows linear programming to be combined with other kinds of algorithms. It extracts new constraints for one subproblem from the dual values of the other subproblem. This paper describes an implementation of Benders Decomposition, in the ECLiPSe ..."
Abstract

Cited by 27 (1 self)
 Add to MetaCart
(Show Context)
Benders Decomposition is a form of hybridisation that allows linear programming to be combined with other kinds of algorithms. It extracts new constraints for one subproblem from the dual values of the other subproblem. This paper describes an implementation of Benders Decomposition, in the ECLiPSe language, that enables it to be used within a constraint programming framework. The programmer is spared from having to write down the dual form of any subproblem, because it is derived by the system. Examples are used to show how problem constraints can be modelled in an undecomposed form. The programmer need only specify which variables belong to which subproblems, and the Benders Decomposition is extracted automatically. A class of minimal perturbation problems is used to illustrate how dierent kinds of algorithms can be used for the dierent subproblems. The implementation is tested on a set of minimal perturbation benchmarks, and the results are analysed.
The N k Problem in Power Grids: New Models, Formulations and Numerical Experiments
, 2008
"... Given a power grid modeled by a network together with equations describing the power flows, power generation and consumption, and the laws of physics, the socalled N − k problem asks whether there exists a set of k or fewer arcs whose removal will cause the system to fail. The case where k is small ..."
Abstract

Cited by 26 (1 self)
 Add to MetaCart
(Show Context)
Given a power grid modeled by a network together with equations describing the power flows, power generation and consumption, and the laws of physics, the socalled N − k problem asks whether there exists a set of k or fewer arcs whose removal will cause the system to fail. The case where k is small is of practical interest. We present theoretical and computational results involving a mixedinteger model and a continuous nonlinear model related to this question.
An approach for strategic supply chain planning under uncertainty based on stochastic 01 programming
 J. of Global Opt
, 2003
"... Abstract. We present a twostage stochastic 01 modeling and a related algorithmic approach for Supply Chain Management under uncertainty, whose goal consists of determining the production topology, plant sizing, product selection, product allocation among plants and vendor selection for raw materia ..."
Abstract

Cited by 24 (1 self)
 Add to MetaCart
Abstract. We present a twostage stochastic 01 modeling and a related algorithmic approach for Supply Chain Management under uncertainty, whose goal consists of determining the production topology, plant sizing, product selection, product allocation among plants and vendor selection for raw materials. The objective is the maximization of the expected benefit given by the product net profit over the time horizon minus the investment depreciation and operations costs. The main uncertain parameters are the product net price and demand, the raw material supply cost and the production cost. The first stage is included by the strategic decisions. The second stage is included by the tactical decisions. A tight 01 model for the deterministic version is presented. A splitting variable mathematical representation via scenario is presented for the stochastic version of the model. A twostage version of a Branch and Fix Coordination (BFC) algorithmic approach is proposed for stochastic 01 program solving, and some computational experience is reported for cases with dozens of thousands of constraints and continuous variables and hundreds of 01 variables.
Algorithms and software for convex mixed integer nonlinear programs
"... This paper provides a survey of recent progress and software for solving convex mixed integer nonlinear programs (MINLP)s, where the objective and constraints are defined by convex functions and integrality restrictions are imposed on a subset of the decision variables. Convex MINLPs have received ..."
Abstract

Cited by 24 (4 self)
 Add to MetaCart
(Show Context)
This paper provides a survey of recent progress and software for solving convex mixed integer nonlinear programs (MINLP)s, where the objective and constraints are defined by convex functions and integrality restrictions are imposed on a subset of the decision variables. Convex MINLPs have received sustained attention in recent years. By exploiting analogies to wellknown techniques for solving mixed integer linear programs and incorporating these techniques into software, significant improvements have been made in the ability to solve these problems.
Strong formulations for network design problems with connectivity requirements
 NETWORKS
, 1999
"... The network design problem with connectivity requirements (NDC) models a wide variety of celebrated combinatorial optimization problems including the minimum spanning tree, Steiner tree, and survivable network design problems. We develop strong formulations for two versions of the edgeconnectivity ..."
Abstract

Cited by 19 (1 self)
 Add to MetaCart
The network design problem with connectivity requirements (NDC) models a wide variety of celebrated combinatorial optimization problems including the minimum spanning tree, Steiner tree, and survivable network design problems. We develop strong formulations for two versions of the edgeconnectivity NDC problem: unitary problems requiring connected network designs, and nonunitary problems permitting nonconnected networks as solutions. We (i) present a new directed formulation for the unitary NDC problem that is stronger than a natural undirected formulation, (ii) project out several classes of valid inequalitiespartition inequalities, oddhole inequalities, and combinatorial design inequalitiesthat generalize known classes of valid inequalities for the Steiner tree problem to the unitary NDC problem, and (iii) show how to strengthen and direct nonunitary problems. Our results provide a unifying framework for strengthening formulations for NDC problems, and demonstrate the strength and power of flowbased formulations for network design problems with connectivity requirements.
A Finite Branch and Bound Algorithm for TwoStage Stochastic Integer Programs
, 2000
"... This paper addresses a general class of twostage stochastic programs with integer recourse and discrete distributions. We exploit the structure of the value function of the second stage integer problem to develop a novel global optimization algorithm. The proposed scheme departs from those in the c ..."
Abstract

Cited by 18 (5 self)
 Add to MetaCart
This paper addresses a general class of twostage stochastic programs with integer recourse and discrete distributions. We exploit the structure of the value function of the second stage integer problem to develop a novel global optimization algorithm. The proposed scheme departs from those in the current literature in that it avoids explicit enumeration of the search space while guaranteeing finite termination. Our computational results indicate superior performance of the proposed algorithm in comparison to the existing literature. Keywords: stochastic integer programming, branch and bound, finite algorithms. 1 Introduction Under the twostage stochastic programming paradigm, the decision variables of an optimization problem under uncertainty are partitioned into two sets. The first stage variables are those that have to be decided before the actual realization of the uncertain parameters. Subsequently, once the random events have presented themselves, further design or operational ...