Eva K. Lee and John E. Mitchell. Computational experience of an interior-point algorithm in a parallel branch-andcut framework. In Proceedings for SIAM Conference on Parallel Processing for Scientific Computing, 1997. Home/Search Document Not in Database Summary Related Articles Check |
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State-of-the-Art in Parallel Search Techniques for Discrete.. - Grama, Kumar (Correct)
....the efficiency of the search but not its correctness. The overhead for maintaining the current best solution tends to be a small fraction of the overhead for dynamic load balancing. Parallel formulations of DFBB have been shown to yield near linear speedups for many problems and architectures [45, 27, 8, 7, 1]. Termination of Parallel Search If only one solution is desired to a problem instance being solved using depth first search, then as soon as any processor finds a solution, search at other processors needs to be terminated. On some parallel architectures, it is possible for one processor to ....
....branch and cut methods, a cut generated at a certain state may be required by other states. Therefore, in addition to balancing load, the parallel branch and cut formulation must also partition cuts among processors so that processors working in certain LP domains have access to the desired cuts [2, 27, 8]. In addition to inter node parallelism that has been discussed until this point, intra node parallelism can become a viable option if the heuristic is computationally expensive. For example, the assignment heuristic of Pekny et al. has been effectively parallelized for solving large instances of ....
Eva K. Lee and John E. Mitchell. Computational experience of an interior-point algorithm in a parallel branch-andcut framework. In Proceedings for SIAM Conference on Parallel Processing for Scientific Computing, 1997.
(minlp): Branch And Bound Methods - General Mixed (Correct)
....in step 3 are convex and thus relatively easy to solve. A variety of methods have been used to solve these subproblems including generalized reduced gradient (GRG) methods [11] sequential quadratic programming (SQP) 4] active set methods for quadratic programming [8] and interior point methods [16]. However, if the nonlinear programming subproblems are nonconvex, then it can be extremely difficult to solve the nonlinear programming relaxation of S or even obtain a lower bound on the optimal objective function value. For some specialized classes of nonconvex optimization problems, including ....
Lee, Eva K., and Mitchell, John E.: `Computational Experience of an Interior Point Algorithm in a Parallel Branch-and-Cut Framework': Proceedings of the Eighth SIAM Conference on Parallel Processing for Scientific Computing, Minneapolis, March 1997,
Load Balancing for Parallel Optimization Techniques - Grama, Kumar (Correct)
.... finds a better solution, it updates this global current best solution (using a broadcast in message passing machines and a lock set in shared memory machines) DFBB and IDA using these parallel DFS algorithms has been shown to yield excellent performance for various optimization problems [19, 13, 3]. In many optimization problems, the successors of nodes tend to be strongly ordered. In such cases, naive parallel formulations that ignore this ordering information will perform poorly since they are likely to expand a much larger subspace than those that explore nodes in the right order. ....
Eva K. Lee and John E. Mitchell. Computational experience of an interior-point algorithm in a parallel branch-and-cut framework. In Proceedings for SIAM Conference on Parallel Processing for Scientific Computing, 1997.
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