This paper presents a parallel hybrid evolutionary algorithm executed in a grid environment. The algorithm executes local searches using Simulated Annealing within a Genetic Algorithm to solve the Job Shop Scheduling Problem. Experimental results of the algorithm obtained in the “Tarantula Mini

. Many problems in industry are a form of openshop scheduling problem (OSSP). We describe a hybrid approach to this problem which combines a Genetic Algorithm (GA) with simple heuristic schedule building rules. Excellent performance is found on some benchmark OSS problems, including improvements

This paper presents a parallel hybrid evolutionary algorithm executed in a grid environment. The algorithm executes local searches using simulated annealing within a Genetic Algorithm to solve the job shop scheduling problem. Experimental results of the algorithm obtained in the “Tarantula Mini

The problem of scheduling several jobs on number of machine with each job having specific machine route has been researched over the decades. This job shop problem is one of the most well-known hardest combinatorial optimization problem. This led to recent interest in using genetic algorithm (GA

ABSTRACT -In this paper a hybrid genetic and harmony search algorithm is proposed to find the possible best sequence of operation solutions for hybrid flow shop scheduling problems. In this work the problem is considered with respect to the objective of minimization of makespan. Hybrid flow shop

April 29, 2011Für UnsShe had never before seen a rabbit with either a waistcoat-pocket, or a watch to take out of it, and burning with curiosity, she ran across the field after it Lewis CarrollThe following document, written under the supervision of Dr. reviewed by:

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In presenting this thesis in partial fulfilment of the requirements for a Postgraduate degree

Abstract: Online learning initia-tives over the past decade have become increasingly comprehen-sive in their selection of courses and sophisticated in their presen-tation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university education on the internet, free of charge, a real possibility. At this pivotal moment it is appropriate to explore the potential for obtaining comprehensive bioinformatics training with currently existing free video resources. This article pre-sents such a bioinformatics curric-ulum in the form of a virtual course catalog, together with editorial commentary, and an assessment of strengths, weaknesses, and likely future directions for open online learning in this field. Online Learning Comes of Age Online academic ‘‘courseware’ ’ at the university level has now been available to the public for a decade, the earliest concerted effort having originated in 2002 with the Massachusetts Institute of Technology (MIT) and their OpenCour-seWare initiative