Branch decomposition-based algorithms have been used in practical settings to solve some NP-hard problems like the travelling salesman problem (TSP) and general minor containment. The notions of branch decompositions and branchwidth were introduced by Robertson and Seymour to assist in proving the Graph Minors Theorem. Given a connected graph G and a branch decomposition of G of width k where k...

We present several heuristic algorithms based on tabu search for solving the multi-stage sequence-dependent group scheduling (SDGS) problem by considering minimization of makespan as the criterion. As the problem is recognized to be strongly NP-hard, several meta (tabu) search-based solution algorithms are developed to efficiently solve industry-size problem instances. Also, two different initi...

The objective of this paper is to analyze the impact of data mapping strategies on the performance of nite element applications. First, we describe a parallel mesh decomposition algorithm based on recursive spectral bisection used to partition the mesh into element blocks. A simple heuristic algorithm then renumbers the mesh nodes. Large three-dimensional meshes demonstrate the eeciency of thos...

We present a new dependency parsing algorithm based on the decomposition of large sentences into smaller units such as clauses and intraclausal coordinations. For the identification of these units, new methods combining machine learning techniques and heuristic rules were developed. The algorithm was evaluated on the Slovene dependency treebank text corpus. Compared to the MSTP parser, currentl...

The earlier the stage where we perform low power design, the higher the dynamic power reduction we achieve. In this paper, we focus on reducing switching activity in high-level synthesis, especially, in the problem of functional module binding, bus binding or register binding. We propose an effective low power bus binding algorithm based on the table decomposition method, to reduce switching ac...

this paper presents a new meta-heuristic solution to find the efficient frontier using the mean-variance approach. portfolio optimization problem is a quadratic programming model and, changes to np-hard if the number of assets and constraints has increased, and it cannot be solved using common mathematical methods in a reasonable time. therefore, a heuristic or meta-heuristic algorithm should b...

this paper addresses the problem of minimizing the sum of maximum earliness and tardiness on identical parallel machines scheduling problem. each job has a processing time and a due date. since this problem is trying to minimize and diminish the values of earliness and tardiness, the results can be useful for just–in-time production systems. it is shown that the problem is np-hard. using effici...