به نام خدا
Title: An efficient B + -tree design for main-memory database systems with strong access locality
Authors: PeiLun Suei a , Victor CS Lee b,fi , ShiWu Lo c , TeiWei Kuo
Abstract: This paper is motivated by the strong demands of many main-memory database applications with strong locality in data access, such as front-end logistical systems. We propose to adopt an auxiliary-tree approach with an tree-merging algorithm to efficiently handle bursty data insertions with keys in a small range and avoid significant overheads in tree rebalancing. A range-based deletion algorithm is then proposed to process data deletions with strong access locality in a batch fashion. The capability of the proposed approach is evaluated by a series of experiments with a wide range of workloads and a variety of locality patterns, where different tree index structures are compared in terms of the performance and memory space requirements.
Publish Year: 2013
Published in: Information Sciences - Science Direct
Number of Pages: 21
موضوع: پایگاه داده (Data Base )
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به نام خدا
Title: Function optimisation by learning automata
Authors: QH Wu , HL Liao
Abstract: This paper presents a new algorithm, Function Optimisation by Learning Automata (FOLA), to solve complex function optimisation problems. FOLA consists of multiple automata, in which each automaton undertakes dimensional search on a selected dimension of the solution domain. A search action is taken on a path which is identified in the search space by the path value, and the path value is updated using the values of the states visited in the past, via a state memory that enables better use of the information collected in the optimisation process. In this paper, FOLA is compared with two popularly used particle swarm optimisers and four newly-proposed optimisers, on nine complex multi-modal benchmark functions. The experimental results have shown that in comparison with the other optimisers, FOLA offers better performance for most of the benchmark functions, in terms of its convergence rate and accuracy, and it uses much less computation time to obtain accurate solutions, especially for high-dimensional functions. In order to explore the FOLA s potential for applications, it is also applied to solve an optimal power flow problem of power systems. FOLA is able to minimise the fuel cost and enhance the voltage stability of the power system more efficiently in comparison with the other algorithms.
Publish Year: 2013
Published in: Information Sciences - Science Direct
Number of Pages: 20
موضوع: اتوماتای یادگیر (Learning Automata )
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به نام خدا
Title: Fractal behind coin-reducing payment
Authors: Ken Yamamoto , Yoshihiro Yamazaki
Abstract: The minimal payment a payment method which minimizes the number of coins in a purse is presented. We focus on a time series of change given back to a shopper repeating the minimal payment. By using the delay plot, the set of successive change possesses a fine structure similar to the Sierpinski gasket. We also estimate affectivity of the minimal- payment method by means of the average number of coins in a purse, and conclude that the minimal-payment strategy is the best to reduce the number of coins in a purse. More- over, we compare our results to the rule-60 cellular automaton and the Pascal Sierpinski gaskets, which are known as generators of the discrete Sierpinski gasket.
Publish Year: 2012
Published in: Chaos, Solitons & Fractals - Science Direct
Number of Pages: 9
موضوع: فرکتال (Fractal)
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به نام خدا
Title: An artificial bee colony algorithm for the maximally diverse grouping problem
Authors: Francisco J Rodriguez , M Lozano a , C GarcaMartnez b , Jonathan D GonzlezBarrera
Abstract: In this paper, an artificial bee colony algorithm is proposed to solve the maximally diverse grouping problem. This complex optimization problem consists of forming maximally diverse groups with restricted sizes from a given set of elements. The artificial bee colony algorithm is a new swarm intelligence technique based on the intelligent foraging behavior of honeybees. The behavior of this algorithm is determined by two search strategies: an initialization scheme employed to construct initial solutions and a method for generating neighboring solutions. More specifically, the proposed approach employs a greedy constructive method to accomplish the initialization task and also employs different neighborhood operators inspired by the iterated greedy algorithm. In addition, it incorporates an improvement procedure to enhance the intensification capability. Through an analysis of the experimental results, the highly effective performance of the proposed algorithm is shown in comparison to the current state-of-the-art algorithms which address the problem.
Publish Year: 2013
Published in: Information Sciences - Science Direct
Number of Pages: 14
موضوع: الگوریتم زنبور عسل (Bee Colony Algorithm)
لینک مقاله در سایت Science Direct
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به نام خدا
Title: Three-stage hybrid-flowshop model for cross-docking
Authors: Adrien Bellanger , Said Hanafl , Christophe Wilbaut
Abstract: This paper deals with the optimization of a cross-docking system. It is modeled as a three-stage hybrid flowshop, in which shipments and orders are represented as batches. The flrst stage corresponds to the receiving docks, the second stage corresponds to the sorting stations, and the third stage corresponds to the shipping docks. The objective of the problem is to flnd a schedule that minimizes the completion time of the latest batch. In order to obtain good quality feasible solutions, we have developed several heuristic schemes depending on the main stage considered, and several rules to order the batches in this stage. Then, we propose a branch-and-bound algorithm that takes into account the decomposition of the problem into three stages. To evaluate the heuristics and to reduce the tree size during the branch-and-bound computation, we also propose lower bounds. Finally, the computational experi- ments are presented to demonstrate the efflciency of our heuristics. The results show that the exact approach can solve instances containing up to 9 10 batches in each stage (i.e., up to 100 jobs). In addition, our heuristics were evaluated over instances with up to 3000 jobs, and they can provide good quality feasible solutions in a few seconds (i.e., less than 2 s per heuristic).
Publish Year: 2013
Published in: Computers & Operations Research - Science Direct
Number of Pages: 10
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