Directional Modulation Transmitter Synthesis using Particle Swarm Optimization

Phased DM transmitter array synthesis using particle swarm optimization (PSO) is presented in this paper. The PSO algorithm is described in details with key parameters provided for 1-D four-element half-wavelength spaced QPSK DM array synthesis. A DM transmitter array for boresight and 30º direction secure communications are taken as examples to validate the proposed synthesis approach. The optimization process exhibits good convergence performance and solution quality.

Business Intelligence and Multi-market Competition

We consider a multi-market framework where a set of firms compete on two oligopolistic markets. The cost of production of each firm allows for spillovers across markets, ensuring that output decisions for both markets have to be made jointly. Prior to competing in these markets, firms can establish links gathering business intelligence about other firms. A link formed by a firm generates two types of externalities for competitors and consumers. We characterize the business intelligence equilibrium networks and networks that maximize social welfare. By contrast with single market competition, we show that in multi-market competition there exist situations where intelligence gathering activities are underdeveloped with regard to social welfare and should be tolerated, if not encouraged, by public authorities.

A Hybrid Swarm Based Approach in Addressing University Timetabling Problems

This paper is concerned with the application of an automated hybrid approach in addressing the university timetabling problem. The approach described is based on the nature-inspired artificial bee colony (ABC) algorithm. An ABC algorithm is a biologically-inspired optimization approach, which has been widely implemented in solving a range of optimization problems in recent years such as job shop scheduling and machine timetabling problems. Although the approach has proven to be robust across a range of problems, it is acknowledged within the literature that there currently exist a number of inefficiencies regarding the exploration and exploitation abilities. These inefficiencies can often lead to a slow convergence speed within the search process. Hence, this paper introduces a variant of the algorithm which utilizes a global best model inspired from particle swarm optimization to enhance the global exploration ability while hybridizing with the great deluge (GD) algorithm in order to improve the local exploitation ability. Using this approach, an effective balance between exploration and exploitation is attained. In addition, a traditional local search approach is incorporated within the GD algorithm with the aim of further enhancing the performance of the overall hybrid method. To evaluate the performance of the proposed approach, two diverse university timetabling datasets are investigated, i.e., Carter's examination timetabling and Socha course timetabling datasets. It should be noted that both problems have differing complexity and different solution landscapes. Experimental results demonstrate that the proposed method is capable of producing high quality solutions across both these benchmark problems, showing a good degree of generality in the approach. Moreover, the proposed method produces best results on some instances as compared with other approaches presented in the literature.

Computational intelligence

The Centre for Intelligent Systems (CIS) is a multidisciplinary research and development centre, founded in 2001, in a very young university, the University of Algarve, in the south of Portugal. The centr's mission is to promote fundamental research in Computational Intelligence (CI) methodology.

Competitive Intelligence : Aufbau einer Informationsbasis und Entscheidungssystematik zur Definition strategischer Zielmärkte

Im Rahmen der Globalisierung und des daraus resultierenden Wettbewerbs ist es für ein Unternehmen von zentraler Bedeutung, Wissen über die Wettbewerbssituation zu erhalten. Nicht nur zur Erschließung neuer Märkte, sondern auch zur Sicherung der Unternehmensexistenz ist eine Wettbewerbsanalyse unabdingbar. Konkurrenz- bzw. Wettbewerbsforschung wird überwiegend als „Competitive Intelligence“ bezeichnet. In diesem Sinne beschäftigt sich die vorliegende Bachelorarbeit mit einem Bereich von Competitive Intelligence. Nach der theoretischen Einführung in das Thema werden die Ergebnisse von neun Experteninterviews sowie einer schriftlichen Expertenbefragung innerhalb des Unternehmens erläutert. Die Experteninterviews und -befragungen zum Thema Competitive Intelligence dienten zur Entwicklung eines neuen Wettbewerbsanalysekonzeptes. Die Experteninterviews zeigten, dass in dem Unternehmen kein einheitliches Wettbewerbsanalysesystem existiert und Analysen lediglich ab hoc getätigt werden. Zusätzlich wird ein Länderranking vorgestellt, das zur Analyse europäischer Länder für das Unternehmen entwickelt wurde. Die Ergebnisse zeigten, dass Dänemark und Italien für eine Ausweitung der Exportgeschäfte bedeutend sind. Der neu entwickelte Mitbewerberbewertungsbogen wurde auf Grundlage dieser Ergebnisse für Dänemark und Italien getestet.