Many cost-based planning heuristics are based on partial or complete delete relaxation. Definitions of these heuristics are of different nature, which makes it difficult to establish relations and formal comparisons among them. In this paper, we propose a unified definition with enough generality to cover most of existing heuristics. Important relations among heuristics can be derived from our ...

Introduction: Various training methods such as web-based tools have been developed to achieve the potential benefits of classification systems by World Health Organization (WHO). Given that users these different levels capability, usability problems could reduce speed and accuracy learning among interacting with tools. This study aims identify under WHO family international classifications (WHO...

Replication and caching strategies are increasingly being used to improve performance and reduce user perceived delays in distributed environments. A query can be answered much faster by accessing a cached copy than by making a database roundtrip. This setting creates a number of important issues such as maintaining consistency among copies of the same data item. Numerous techniques have been p...

In recent years, there has been a growing research interest in integrating machine learning techniques into meta-heuristics for solving combinatorial optimization problems. This integration aims to lead toward an efficient, effective, and robust search improve their performance terms of solution quality, convergence rate, robustness. Since various methods with different purposes have developed,...

An important problem in large-scale wide-area networks is to provide communication facilities for nodes of a distributed application that are attached to various machines in the network. Providing connectivity among a set of application nodes in a network can be modeled as the Steiner tree problem which is an NP-complete problem. Although several heuristics have been proposed in the literature,...

Compiler writers are expected to create effective and inexpensive solutions to NP-hard problems such as instruction scheduling and register allocation. To make matters worse, separate optimization phases have strong interactions and competing resource constraints. Compiler writers deal with system complexity by dividing the problem into multiple phases and devising approximate heuristics for ea...

Companies operate by setting goals in various business fields, and then taking action to achieve those goals. Optimization techniques are one way to obtain operation (decision making) that will, to the extent possible, approach goals that have been set in response to a given problem. As a result, solutions such as designs for minimal operating cost, optimal product quality, smallest device size...

In this paper, we present a generic hybrid algorithm for combining complete (constraint programming) and incomplete (local search) methods in order to solve constraint satisfaction problems. This algorithmic scheme uses constraint propagation techniques and local search heuristics over populations. The structures involved provide an harmonious interaction between the different methods, and also...

Local algorithms for obtaining pivot orderings for sparse symmetric coefficient matrices are reviewed together with their mathematical background, appropriate data structures and details of efficient implementation. Heuristics that go beyond the classical Minimum Degree and Minimum Local Fill scoring functions are discussed, illustrated, improved and extensively tested on a test suite of matric...