Mine scheduling is a multi-objective highly constrained optimization problem. Often months are spent by mine planners to achieve one feasible ore production solution. In order to assist in the process and to present a...
详细信息
ISBN:
(纸本)0889865361
Mine scheduling is a multi-objective highly constrained optimization problem. Often months are spent by mine planners to achieve one feasible ore production solution. In order to assist in the process and to present alternatives with a higher likelihood of optimality, a parallel genetic algorithm for long-term scheduling of underground mines is developed. For the mine scheduling problems considered, a 2-dimensional map of stopes is given, along with the mineral properties of each. It is required to schedule the extraction sequence of the ore from the stopes to meet the mine's objectives. The appropriateness of a schedule is determined by applying a fitness function. The fitness function assesses how well the schedule meets objectives and satisfies given constraints. In practice, the scheduling problem is simplified in order to obtain a solution in given time bounds. By modularizing the problem and employing a parallel algorithm with minimal communication requirements, a higher quality mine schedule may be found in given time bounds.
Stabilized explicit implicit domain decomposition (SEIDD) is a class of globally non-iterative domain decomposition methods for the numerical simulation of unsteady diffusion processes on parallel computers. By adding...
详细信息
ISBN:
(纸本)0769523129
Stabilized explicit implicit domain decomposition (SEIDD) is a class of globally non-iterative domain decomposition methods for the numerical simulation of unsteady diffusion processes on parallel computers. By adding a communication-cost-free stabilization step to the explicit-implicit domain decomposition (EIDD) methods, the SEIDD methods achieve high stability but with the restriction that the interface boundaries have no crossing-overs inside the domain. In this paper, we present a parallelized SEIDD algorithm with paralellism higher than the number of subdomains, eliminating the disadvantage of non-crossing-over interface boundaries at a slight computation cost.
We consider three approaches for estimating the rates of nonsynonymous and synonymous changes at each site in a sequence alignment in order to identify sites under positive or negative selection: (1) a suite of fast l...
详细信息
We consider three approaches for estimating the rates of nonsynonymous and synonymous changes at each site in a sequence alignment in order to identify sites under positive or negative selection: (1) a suite of fast likelihood-based "counting methods" that employ either a single most likely ancestral reconstruction, weighting across all possible ancestral reconstructions, or sampling from ancestral reconstructions;(2) a random effects likelihood (REL) approach, which models variation in nonsynonymous and synonymous rates across sites according to a predefined distribution, with the selection pressure at an individual site inferred using an empirical Bayes approach;and (3) a fixed effects likelihood (FEL) method that directly estimates nonsynonymous and synonymous substitution rates at each site. All three methods incorporate flexible models of nucleotide substitution bias and variation in both nonsynonymous and synonymous substitution rates across sites, facilitating the comparison between the methods. We demonstrate that the results obtained using these approaches show broad agreement in levels of Type I and Type 11 error and in estimates of substitution rates. Counting methods are well suited for large alignments, for which there is high power to detect positive and negative selection, but appear to underestimate the substitution rate. A REL approach, which is more computationally intensive than counting methods, has higher power than counting methods to detect selection in data sets of intermediate size but may suffer from higher rates of false positives for small data sets. A FEL approach appears to capture the pattern of rate variation better than counting methods or random effects models, does not suffer from as many false positives as random effects models for data sets comprising few sequences, and can be efficiently parallelized. Our results suggest that previously reported differences between results obtained by counting methods and random effects models a
An efficient parallel algorithm is presented to find a maximum weight independent set of a permutation graph which takes O(log n) time using O(n(2)/log n) processors on an EREW PRAM, provided the graph has at most O(n...
详细信息
An efficient parallel algorithm is presented to find a maximum weight independent set of a permutation graph which takes O(log n) time using O(n(2)/log n) processors on an EREW PRAM, provided the graph has at most O(n) maximal independent sets. The best known parallel algorithm takes O(log(2) n) time and O(n(3)/log n) processors on a CREW PRAM.
Genetic sequence data typically exhibit variability in substitution rates across sites. In practice. there is often too hale, variation to fit a different rate for each site in the alignment. but the distribution of r...
详细信息
Genetic sequence data typically exhibit variability in substitution rates across sites. In practice. there is often too hale, variation to fit a different rate for each site in the alignment. but the distribution of rates across sites may not be well modeled using simple parametric families. Mixtures of different distributions can capture more complex patterns of rate variation, but are often parameter-rich and difficult to fit. We present a simple hierarchical model in which a baseline rate distribution, such as a gamma distribution. is discretized into several categories, the quantiles of which are estimated using a discretized beta distribution. Although this approach involves adding only two extra parameters to a standard distribution, a wide range of rate distributions can be captured. Using simulated data, we demonstrate that a "beta-" model can reproduce the moments of the rate distribution more accurately than the distribution used to simulate the data. even when the baseline rate distribution is misspecified. Using hepatitis C virus and mammalian mitochondrial sequences, we show that a beta-model can fit as well or better than a model with multiple discrete rate categories. and compares favorably with a model which fits a separate rate category to each site. We also demonstrate this discretization scheme in the context of codon models specifically aimed at identifying individual sites undergoing adaptive or purifying evolution.
Power-List, ParList and PList data structures are efficient tools for functional descriptions of parallel programs that are divide & conquer in nature. The goal of this work is to develop three parallel variants f...
详细信息
ISBN:
(纸本)3540440496
Power-List, ParList and PList data structures are efficient tools for functional descriptions of parallel programs that are divide & conquer in nature. The goal of this work is to develop three parallel variants for Fast Fourier Transformation using these theories. The variants are implied by the degree of the polynomial, which can be a power of two, a prime number, or a product of prime factors. The last variant includes the first two, and represents a general and efficient parallel algorithm for Fast Fourier Transformation. This general algorithm has a very good time complexity, and can be mapped on a recursive interconnection network.
To improve the solving efficiency of standard genetic algorithms, a parallel multi-deme adaptive genetic algorithm is proposed based on six fuzzy logic controllers (6FLC-MDPFGA). A PC cluster of workstation (COW) usin...
详细信息
To improve the solving efficiency of standard genetic algorithms, a parallel multi-deme adaptive genetic algorithm is proposed based on six fuzzy logic controllers (6FLC-MDPFGA). A PC cluster of workstation (COW) using the message passing interface (MPI) technology is built. Furthermore, the 6FLC-MDPFGA is realized on the hardware platform. When the possibility of the algorithm design is illustrated, results from initial experiments on the 3 PCs COW platform indicate that the algorithm efficiency is improved. Meanwhile, experiments show that the multi-deme algorithm can provide more stable results. The algorithm is run on the 3 PCs COW platform, and easily implemented on a large-scale PCs COW platform using MPf. The 6FLC-MDPFGA can be applied to a wide range of combinatorial optimization. Finally, how to select parameters is discussed.
In the group mutual exclusion problem [Y Joung, Asynchronous group mutual exclusion, Distrib. Comput. 13 (2000) 189], which generalizes mutual exclusion [E. Dijkstra, Solution of a problem in concurrent programming co...
详细信息
In the group mutual exclusion problem [Y Joung, Asynchronous group mutual exclusion, Distrib. Comput. 13 (2000) 189], which generalizes mutual exclusion [E. Dijkstra, Solution of a problem in concurrent programming control, Comm. ACM 8 (9) (1965) 569], a process chooses a session when it requests entry into the Critical Section. A group mutual exclusion algorithm must ensure that the mutual exclusion property holds: if two processes are in the Critical Section at the same time, then they request the same session. In addition to mutual exclusion, lockout freedom, bounded exit, and concurrent entering are basic properties that are desirable in any group mutual exclusion algorithm. Hadzilacos in [Proc. 20th Annual Symp. on Principles of Distributed Computing, 2001, pp. 100-106] first introduced a fairness condition, called first-come-first-served (FCFS), for group mutual exclusion. The only known FCFS group mutual exclusion algorithm is due to Hadzilacos [Proc. 20th Annual Symp. on Principles of Distributed Computing, 2001, pp. 100-106], and requires Theta(N-2) bounded shared registers, where N is the number of processes. We present a FCFS group mutual exclusion algorithm that uses only Theta(N) bounded shared registers. (The existence of such an algorithm was posed as an open problem by Hadzilacos.) (c) 2005 Elsevier B.V. All rights reserved.
According to the characteristics of large scale finite element method (FEM) paralleling processing on cluster computers, an optimized automatic partition approach-modified multilevel recursive spectral bisection (MRSB...
详细信息
According to the characteristics of large scale finite element method (FEM) paralleling processing on cluster computers, an optimized automatic partition approach-modified multilevel recursive spectral bisection (MRSB) is proposed. This approach is based on modification in coarsening, partition and refinement phases of multilevel recursive spectral bisection. The vertex balancing strategy (VBS) and balancing Kernighan-Lin (BKL) method are proposed and the shortcomings of multilevel recursive spectral bisection (MRSB) are overcome. It is also applied to practical problems of different geometry. The partition results show that the proposed method is valid and significant improvement is achieved.
In this paper we present an evaluation of selected parallel strategies for Simulated Annealing and Simulated Evolution, identifying the impact of various issues on the effectiveness of parallelization. Issues under co...
详细信息
ISBN:
(纸本)1595930108
In this paper we present an evaluation of selected parallel strategies for Simulated Annealing and Simulated Evolution, identifying the impact of various issues on the effectiveness of parallelization. Issues under consideration are the characteristics of these algorithms, the problem instance, and the implementation environment. Observations are presented regarding the impact of parallel strategies on runtime and achievable solution quality. Effective parallel algorithm design choices are identified, along with pitfalls to avoid. We further attempt to generalize our assessments to other heuristics.
暂无评论