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132
Computational Experience of an Interior-Point SQP Algorithm in a Parallel Branch-and-Bound Framework
"... An interior-point algorithm within a parallel branch-and-bound framework for solving nonlinear mixed integer programs is described. The nonlinear programming relaxations at each node are solved using an interior point SQP method. In contrast to solving the relaxation to optimality at each tree node ..."
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Cited by 11 (3 self)
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An interior-point algorithm within a parallel branch-and-bound framework for solving nonlinear mixed integer programs is described. The nonlinear programming relaxations at each node are solved using an interior point SQP method. In contrast to solving the relaxation to optimality at each tree
A Branch-and-Bound Algorithm for Array Distributions
"... An important problem facing parallelizing compilers for distributed memory mimd machines is that of distributing data across processors. This distribution affects the amout of data movements among processors that is required to execute the computations of the input program. This work proposes a bran ..."
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branch--and--bound based method to automatically compute a distribution for the arrays of the input program. The method is able to arrange redistributions of data during program execution. To test the proposed method, we have embedded it into an experimental parallelizing compiler for an Intel iPSC=860
Parallel Branch-and-Bound for Two-Stage Stochastic Integer Optimization
"... Abstract---Many real-world planning problems require search-ing for an optimal solution in the face of uncertain input. One approach to is to express them as a two-stage stochastic optimization problem where the search for an optimum in one stage is informed by the evaluation of multiple possible sc ..."
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scenarios in the other stage. If integer solutions are required, then branch-and-bound techniques are the accepted norm. However, there has been little prior work in parallelizing and scaling branch-and-bound algorithms for stochastic optimization problems. In this paper, we explore the parallelization of a
Ancestral Benders’ Cuts and Multi-term Disjunctions for Mixed-Integer Recourse Decisions in Stochastic Programming
, 2013
"... This paper focuses on solving two-stage stochastic mixed integer programs (SMIPs) with general mixed integer decision variables in both stages. We develop a decomposition algorithm in which the first stage approximation is solved using a branch-and-bound tree with nodes inheriting Benders’ cuts that ..."
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Cited by 1 (0 self)
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This paper focuses on solving two-stage stochastic mixed integer programs (SMIPs) with general mixed integer decision variables in both stages. We develop a decomposition algorithm in which the first stage approximation is solved using a branch-and-bound tree with nodes inheriting Benders’ cuts
Resource Management in a Parallel Mixed Integer Programming Package
, 1997
"... This paper describes resource management in a massively parallel, distributed-memory implementation of a branch-and-bound method for mixed integer programming (MIP) problems. Our parallel branch-and-bound algorithm decomposes into a variety of interacting but largely asynchronous tasks. These tasks ..."
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Cited by 7 (6 self)
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This paper describes resource management in a massively parallel, distributed-memory implementation of a branch-and-bound method for mixed integer programming (MIP) problems. Our parallel branch-and-bound algorithm decomposes into a variety of interacting but largely asynchronous tasks. These tasks
Decomposition with Branch-and-Cut Approaches for Two Stage Stochastic Mixed-Integer Programming
, 2004
"... Decomposition has proved to be one of the more effective tools for the solution of large scale problems, especially those arising in stochastic programming. A decomposition method with wide applicability is Benders ’ decomposition, and has been applied to both stochastic programming, as well as inte ..."
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Cited by 24 (2 self)
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Programming (SMIP) problems can be solved by dividing a large problem into smaller MIP subproblems which can be solved in parallel. This paper lays the foundation for such decomposition methods for two-stage stochastic integer programs. Decomposition with Branch-and-Cut Approaches for Two Stage Stochastic
In Search of a Scalable, Parallel Branch-and-Bound for Two-Stage Stochastic Integer Optimization
"... Abstract—Many real-world planning problems require searching for an optimal solution in the face of uncertain input. One approach to is to express them as a two-stage stochastic optimization problem where the search for an optimum in one stage is informed by the evaluation of multiple possible scena ..."
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scenarios in the other stage. If integer solutions are required, then branchand-bound techniques are the accepted norm. However, there has been little prior work in parallelizing and scaling branch-andbound algorithms for such problems. In this paper, we explore the parallelization of a two-stage stochastic
Branch and Bound Based Coordinate Search Filter Algorithm for Nonsmooth Nonconvex Mixed-Integer Nonlinear Programming Problems
"... Abstract. A mixed-integer nonlinear programming problem (MINLP) is a problem with continuous and integer variables and at least, one nonlinear function. This kind of problem appears in a wide range of real applications and is very difficult to solve. The difficulties are due to the nonlinearities of ..."
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Abstract. A mixed-integer nonlinear programming problem (MINLP) is a problem with continuous and integer variables and at least, one nonlinear function. This kind of problem appears in a wide range of real applications and is very difficult to solve. The difficulties are due to the nonlinearities
A Lagrangean based Branch-and-Cut algorithm for global optimization of nonconvex Mixed-Integer Nonlinear Programs with decomposable structures
, 2006
"... In this work we present a global optimization algorithm for solving a class of large-scale nonconvex optimization models that have a decomposable structure. Such models are frequently encountered in two-stage stochastic programming problems, engineering design, and also in planning and scheduling. A ..."
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Cited by 3 (1 self)
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. A generic formulation and reformulation of the decomposable models is given. We propose a specialized deterministic branch-and-cut algorithm to solve these models to global optimality, wherein bounds on the global optimum are obtained by solving convex relaxations of these models with certain cuts
Chapter 5 PARALLEL ALGORITHM DESIGN FOR BRANCH AND BOUND
"... Abstract Large and/or computationally expensive optimization problems sometimes require parallel or high-performance computing systems to achieve reasonable running times. This chapter gives an introduction to parallel computing for those familiar with serial optimization. We present techniques to a ..."
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on these platforms. As concrete examples, we discuss the design of parallel branch-and-bound algorithms for mixed-integer programming on a distributed-memory system, quadratic assignment problem on a grid architecture, and maximum parsimony in evolutionary trees on a shared-memory system.
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