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We introduce the notion of Optimal Patterns (OPs), defined as the best patterns according to a given user preference, and show that OPs encompass many data mining problems. Then, we propose a generic method based on a Dynamic Constraint Satisfaction Problem to mine OPs, and we show that any OP is characterized by a basic constraint and a set of constraints to be dynamically added. Finally, we perform...
Gravitational Search Algorithm (GSA) is a population-based optimization algorithm based on Newton's law of gravity and the notion of mass interactions. GSA has the advantage of proper global search ability. However, it suffers from weak local search due to relatively big step-size of agents in the search process. In order to improve the balance between exploration and exploitation of GSA, two mechanisms...
Ant two-way parallel searching strategy is adopted to accelerate searching speed, but it is clearly seen that this tactic loses some feasible paths and even loses optimal path, so a new ants meeting judgment method is proposed in this paper. At the same time pheromone gain is added to allocate initial pheromone reasonably in order to deal with slow searching speed brought by equivalence distributing...
Many search space generation algorithms used by query optimizers focus on efficiently and exhaustively enumerating the set of alternative plans. However, newly emerged systems, such as Object-Relational Mapping (ORM) tools, introduce new challenges to the query optimizer. This is because dynamically generated queries are very complex, relatively inexpensive to execute, and they must be optimized at...
Conjugate gradient methods are well known and popular in unconstrained optimization. Numerous studies and modifications have been devoted by researchers to improve this method. In this paper, we introduced a new conjugate gradient coefficient (βk) and tested its performance using exact line search. Numerical results based on number of iterations have shown our new βk performance is better or equivalent...
The study aims at Supermarket Distribution Problem, a mathematical model is constructed and an ant colony algorithm with tabu search is put forward. The algorithm is tested in combination with Supermarket Distribution Problem. The experimental results indicated that the algorithm solves Supermarket Distribution Problem effectively with quick convergence, avoids local optimum, high precision solution...
A comprehensive optimal regulation model for distribution networks is presented, which utilizes the reactive power regulating means, sectionalizing and tie switchers to reduce active power losses. A loop-based coding scheme is proposed for reconfiguration description. The reactive tabu search algorithm is employed to get the optimal solution. The efficiency of the proposed method is identified by...
Parallel metaheuristics based on Multiple Independent Runs (MIR) and cooperative search algorithms are widely used to solve difficult optimization problems in diverse domains. A key step in assessing and improving the speed of global convergence of parallel metaheuristics is tracing solutions explored by the MIR-based algorithm. However, this generates large amounts of data, thus posing execution...
This paper addresses the problem of integration testing of data-centric dynamic compositions in service-based systems. These compositions define abstract services, which are replaced by invocations to concrete candidate services at runtime. Testing all possible runtime instances of a composition is often unfeasible. We regard data dependencies between services as potential points of failure, and introduce...
This paper presents a novel resource allocation procedure for OFDMA downlinks, which stems from an hybridization of the Harmony Search and the Differential Evolution heuristic algorithms. In this setup it is known that optimum subcarrier and power allocation is achieved through 1) assigning each subcarrier to the user with highest channel gain at the given frequency, and 2) a Water-Filling procedure...
Multi objective multi contradiction task selection is an important and complex problem, and affects the benefit and the development of the enterprise remarkably. The mathematics mode of multi objective multi contradiction task selection problem is set up. The search method based on the elasticity is put forward. The mode and the method put forward are applied to solve two instances and optimal results...
A redundancy allocation method based on reusable patterns to optimize system reliability and maintainability (via series MTBF) is presented. Reusable patterns are “learned experiences” that are traceable and can enhance computational efficiency. This paper addresses the essential issues of this approach, and examples are implemented using object-oriented C++.
The SAGE algorithm gives the chance to divide the multi-dimension optimization problem, which one confronts when the maximum likelihood (ML) estimation is performed, into iterations of one-dimension optimization problems. The progress to find out the maximum of the log-likelihood function during Maximization-step (M-step) of the algorithm is yet to be refined with purpose of reducing the time cost...
In this paper, we have proposed a novel algorithm based on Ant Colony Optimization (ACO) for finding near-optimal solutions for the Multi-dimensional Multi-choice Knapsack Problem (MMKP). MMKP is a discrete optimization problem, which is a variant of the classical 0-1 Knapsack Problem and is also an NP-hard problem. Due to its high computational complexity, exact solutions of MMKP are not suitable...
In many real-world applications, the accurate number of clusters in the data set may be unknown in advance. In addition, clustering criteria are usually high dimensional, nonlinear and multi-model functions and most existing clustering algorithms are only able to achieve a clustering solution that locally optimizes them. Therefore, a single clustering criterion sometimes fails to identify all clusters...
Traditional approaches to apply tabu search method typically require formulating an algorithmic structure for each individual problem. Based on algebraic specifications, the paper presents a unified and mechanical framework for implementing tabu search algorithms for combinatorial optimization problems. We define a generalized specification using high-order functions to describe search strategies,...
The proposed work presented a modified MAX-MIN Ant System (MMAS) algorithm to solve the routing problem, in which known demand are supplied from a store house with parallel routes for new local search. Routing Problem is an optimization problem and solved to nearly optimum by heuristics. The objective of routing issues is to use a fleet of vehicles with specified capacity to serve a number of users...
The goal of this research is to find how dependencies affect the capability of several feature selection approaches to extract of the relevant features for a classification purpose. The hypothesis is that more dependencies and higher level dependencies mean more complexity for the task. Some experiments are used to intend to discover some limitations of several feature selection approaches by altering...
In this paper, the total transmission power of a multi-source multi-destination relay network is minimized under the constraint that the signal to interference plus noise ratio (SINR) requirement of each source-destination pair is satisfied. The optimization problem involves K power variables, where K is the number of source-destination pairs in the network, and an exhaustive search is prohibitive...
In CBR system, the case base is becoming increasingly larger with the incremental learning which results in the decline of case retrieval efficiency and its weaker performance. Aiming at such weakness of CBR system, this article proposes a novel case retrieval method based on Hybrid Ant-Fish Clustering Algorithm (HA-FC). At beginning of algorithm, we get rough cluster sets utilizing the advantage...
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