The paper presents a new powerful technique to linearize the quadratic assignment problem. There are so many techniques available in literature that used In all these linear formulations, both number of variables and constraints significantly increase. problem (QAP) is well-known whereby set facilities allocated locations such way cost function distance flow between facilities. this problem, co...

Introduct ion The TACITUS system uses a cost-based abduction scheme for finding and choosing among possible interpretations for natural language texts. Ordinary Prologstyle, backchaining deduction is augmented with the capability of making assumptions and of factoring two goal literals that are unifiable (see Hobbs et al., 1988). Deduction is combinatorially explosive, and since the abduction s...

Multi-constraint quality-of-service routing will become increasingly important as the Internet evolves to support real-time services. It is well known however, that optimum multi-constraint QoS routing is computationally complex, and for this reason various heuristics have been proposed for routing in practical situations. Among these methods, those that use a single mixed metric are the most p...

Abstr act. This paper st udies differences and similarit ies among inductive GMDH, deductive adaline, and back prop agat ion techniques. All these are considered as parallel opt imizat ion algorithms because each one minimizes the out put residual error in its own way. Selforganizing processes and criteria that help obta in the optimum output responses in the algorithms are explained through th...

DLV is the state-of-the-art system for evaluating disjunctive answer set programs. As in most Answer Set Programming (ASP) systems, its implementation is divided in a grounding part and a propositional model-finding part. In this paper, we focus on the latter, which relies on an algorithm using backtracking search. Recently, DLV has been enhanced with backjumping techniques, which also involve ...

In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a c...

In modern biology, digitization of biosystematics publications is an important task. Extraction of taxonomic names from such documents is one of its major issues. This is because these names identify the various genera and species. This article reports on our experiences with learning techniques for this particular task. We say why established Named-Entity Recognition techniques are somewhat di...

Travelling salesman problem (TSP) is a combinatorial optimization problem. It is NP hard problem and TSP is the most intensively studied problem in the area of optimization. There are a number of approximation algorithms and heuristics proposed in the literature which can yield to good solutions. But with the increase in the number of cities, the complexity of the problem goes on increasing. Th...

Abstract The collective behaviour of fish schools, shoals and other swarms in nature has long inspired researchers to develop solutions for optimization problems. Instinct influences the group into schools increase safety, enhance foraging success, promote breeding. According these instinctive behaviours, several fish-inspired algorithms have been introduced solve hard This paper presents a com...