Computer communications

This first chapter intends to review and analyze the powerful new Harmony Search (HS) algorithm in the context of metaheuristic algorithms. We will first outline the fundamental steps of HS, and show how it works. We then try to identify the characteristics of metaheuristics and analyze why HS is a good metaheuristic algorithm. We then review briefly other popular metaheuristics such as particle swarm optimization so as to find their similarities and differences with HS. Finally, we will discuss the ways to improve and develop new variants of HS, and make suggestions for further research including open questions.

Music-Inspired Harmony Search Algorithm

Flooding-limited and multi-constrained QoS multicast routing based on the genetic algorithm for MANETs

Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing

Vehicular Ad hoc NETworks (VANETs) play a key role in the design and development of Intelligent Transportation Systems (ITS) that aim to improve road safety and transportation productivity VANETs cover vehicle-to-vehicle and vehicle-to-roadside communications One of the most important challenges of this type of network is the timely and reliable dissemination of messages among vehicular nodes that enable drivers to take appropriate decisions to improve road safety In the past decade, many routing protocols for VANETs that can support reliability and safety requirements have been proposed These protocols suffer from several limitations, including complexity, lack of scalability to large scale networks, routing overheads, etc To address these limitations, various bio-inspired approaches have been proposed to route packets among vehicular nodes in an optimized manner We survey recent proposed bio-inspired routing algorithms for the VANET environment In particular, we identify the key features, strengths, and weaknesses of these algorithms and compare them by using various criteria Moreover, we propose a unified formal model of the bio-inspired multimodular approaches applied to VANET routing We highlight main future research directions in this area

Bio-Inspired Routing Algorithms Survey for Vehicular Ad Hoc Networks

A system is developed for recognition of handwritten Farsi/Arabic characters and numerals. The discrete wavelet transform is utilized to produce wavelet coefficients, which are used for classification. We used Haar wavelet for feature extraction in this system. The extracted features are used as training inputs to a feed forward neural network using the backpropagation learning rule. The learning and test patterns were gathered from various people with different educational backgrounds and different ages. We categorize 32 characters in Farsi language to 8 different classes in which characters of each class are very similar to each others. There are ten digits in Farsi/Arabic languages, but two of them are not used in postal codes in Iran, so we have 8 different extra classes for digits. This system yields the classification rates of 92.33% and 91.81% for these 8 classes of handwritten Farsi characters and numerals respectively. We used this system for recognizing the handwritten postal addresses which contain the names of cities and their postal codes. Our database contains 579 postal addresses in Iran. The system yields a recognition rate of 97.24% for these postal addresses.

Feature extraction with wavelet transform for recognition of isolated handwritten Farsi/Arabic characters and numerals

GA-based heuristic algorithms for bandwidth-delay-constrained least-cost multicast routing

Computing the bandwidth-delay-constrained least-cost multicast routing tree is an NP-complete problem. In this paper, we propose a novel QoS-based multicast routing algorithm based on the genetic algorithms (GA). In the proposed algorithm, the connectivity matrix of edges is used for genotype representation. Some novel heuristics are also proposed for mutation, crossover, and creation of random individuals. We evaluate the performance and efficiency of the proposed GA-based algorithm in comparison with other existing heuristic and GA-based algorithms by the result of simulation. The proposed algorithm has overcome all of the previous algorithms in the literature.

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GA-based heuristic algorithms for QoS based multicast routing

We propose a system for recognition of isolated handwritten Persian/Arabic characters and numerals. Wavelet transform has been used for feature extraction in this system using Haar wavelet. The support vector machine (SVM), which is a new learning machine with very good generalization ability, and has been used widely in pattern recognition and regression estimation, uses as classifier in this system. The training and test patterns were gathered from various people with different ages and different educational backgrounds. The 32 characters in Persian language were categorized into 8 different classes in which characters of each class are very similar to each other. There are ten digits in Persian/Arabic languages where two of them are not used in zip codes in Iran. So, we have 8 different extra classes for digits. This system was used for recognizing the isolated handwritten postal addresses, which contain the name of cities and their zip codes. Our database contains 579 postal addresses in Iran. The system yields the recognition rate of 98.96% for these postal addresses. The results show an increment in recognition rates in comparison with our previous work in which we used the MLP neural network as classifier.

Recognition of isolated handwritten Persian/Arabic characters and numerals using support vector machines

The bandwidth-delay-constrained least-cost multicast routing is a challenging problem in high-speed multimedia networks. Computing such a constrained Steiner tree is an NP-complete problem. In this paper, we propose a novel QoS-based multicast routing algorithm based on the genetic algorithms (GA). In the proposed method, Prufer number is used for genotype representation. Some novel heuristic algorithms are also proposed for mutation, crossover, and creation of random individuals. We evaluate the performance and efficiency of the proposed GA-based algorithm in comparison with other existing heuristic and GA-based algorithms by the result of simulation. This proposed algorithm has overcome all of the previous algorithms in the literatures.

A. Mowlaei

Papers

Feature extraction with wavelet transform for recognition of isolated handwritten Farsi/Arabic characters and numerals

GA-based heuristic algorithms for bandwidth-delay-constrained least-cost multicast routing

GA-based heuristic algorithms for QoS based multicast routing

Recognition of isolated handwritten Persian/Arabic characters and numerals using support vector machines

A Genetic Algorithm for Steiner Tree Optimization with Multiple Constraints Using Prüfer Number