Genetic algorithm is a commonly used bio-heuristic optimization algorithm in machine learning, with inherent hidden parallelism and good global optimization capability. In this paper, genetic algorithm is applied to t...
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In our previous work [1], we introduced a technique for reordering prefix codes, enabling direct access functionality without the need for additional storage. In this paper, we extend our previous work [1] into intege...
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We propose a method for efficient handling string constraints with string-integer conversions. It extends the recently introduced stabilization-based procedure for solving string (dis)equations with regular and length...
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In decision-making problems, a situation often arises when a decision maker cannot confidently determine the goal function. This may be due to both the peculiarities of human thinking and incompleteness and inaccuracy...
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This work considers the optimal design of MapReduce-based coded distributed computing (CDC) with nonuniform input file sizes. We propose an efficient heterogeneous CDC (HetCDC) scheme capable of handling an arbitrary ...
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Using a use-case approach, we go into the specific ontology development, adding semantic rules to enhance its formulation and resolution. Our methodology seeks to capture the heterogeneity, variety, and complexity of ...
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In this paper, we address the minimization of open stacks problem (MOSP). This problem often appears during production planning of manufacturing industries, such as in the cutting of objects to comply with space const...
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In this paper, we address the minimization of open stacks problem (MOSP). This problem often appears during production planning of manufacturing industries, such as in the cutting of objects to comply with space constraints around the cutting machine in the glass, furniture, and metallurgical industries. During the processing of the cutting patterns, all the copies of a demanded item are stored in a stack usually placed near the cutting machine. One stack for each type of demanded item, that is, different items do not share the same stack. In this sense, the MOSP consists of finding an optimal sequence of a given set of cutting patterns, while minimizing the maximum number of simultaneously open stacks. To effectively model and solve the problem, we present a novel integer linear programming (ILP) formulation based on a graph representation of the problem. We derive an ILP formulation from the modeling approach of Faggioli and Bentivoglio for the MOSP. Then we develop a simple constraint programming model based on interval variables and renewable resources. We performed computational experiments to evaluate the proposed approaches in comparison with other ILP formulations from the literature. Using a general-purpose solver, the proposed approaches perform well in terms of solution quality and computational time in comparison to the benchmark models for small and moderate-sized problem instances.
With the demand for energy-efficient and high-performance computing, multicore architecture has become more appealing than ever. Multicore task scheduling is one of domains in parallel computing which exploits the par...
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With the demand for energy-efficient and high-performance computing, multicore architecture has become more appealing than ever. Multicore task scheduling is one of domains in parallel computing which exploits the parallelism of multicore. Unlike traditional scheduling, multicore task scheduling has recently been studied on the assumption that tasks have inherent parallelism and can be split into multiple sub-tasks in data parallel fashion. However, it is still challenging to properly determine the degree of parallelism of tasks and mapping on multicores. Our proposed scheduling techniques determine the degree of parallelism of tasks, and sub-tasks are decided which type of cores to be assigned to heterogeneous multicores. In addition, two approaches to hardware/software codesign for heterogeneous multicore systems are proposed. The works optimize the types of cores organized in the architecture simultaneously with scheduling of the tasks such that the overall energy consumption is minimized under a deadline constraint, a warm start approach is also presented to effectively solve the problem. The experimental results show the simultaneous scheduling and core-type optimization technique remarkably reduces the energy consumption.
In this paper, we solve virtualized passive optical network (VPON) assignment and virtualized baseband unit (vBBU) placement using an integer linear programming formulation, an approximated heuristic using linear rela...
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In this paper, we solve virtualized passive optical network (VPON) assignment and virtualized baseband unit (vBBU) placement using an integer linear programming formulation, an approximated heuristic using linear relaxation, and a proactive heuristic based on a specific kind of recurrent neural network. We also studied the application of multi-step forecasting in Cloud-Fog Radio Access Network (CF-RAN) traffic demands for joint use with integer linear programming once it allows the solver more time to generate solutions. Also, we examine if the error in batch prediction impacts the final solution in terms of blocking and correctness.
A radio k-labeling of a graph G is an assignment of non-negative integers (labels) to the vertices of G such that the absolute value of the difference between the labels of any two distinct vertices u and v is not les...
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A radio k-labeling of a graph G is an assignment of non-negative integers (labels) to the vertices of G such that the absolute value of the difference between the labels of any two distinct vertices u and v is not less than k+1-d(u, v), where d(u, v) denotes the distance between u and v. The radio k-labeling number of G is the minimum span of a radio k -labeling of G. For a given set of integers D = {d(1), d(2), ... , dt}, the distance graph G(Z, D), denoted also by D(d(1), d(2), ... , dt), has the set of integers Z as its vertex set, while two distinct vertices i, j epsilon Z are adjacent in G(Z, D) if and only if |i -j| epsilon D. Radio k-labelings of three families of distance graphs are considered. Some improved theoretical lower and upper bounds on the radio k-labeling number are presented and some computer-based methods for computing radio k-labelings of these families of graphs are proposed. (c) 2021 Elsevier B.V. All rights reserved.
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