Cellular Harmony Search for Optimization Problems

Structured population in evolutionary algorithms (EAs) is an important research track where an individual only interacts with its neighboring individuals in the breeding step. The main rationale behind this is to provide a high level of diversity to overcome the genetic drift. Cellular automata concepts have been embedded to the process of EA in order to provide a decentralized method in order to preserve the population structure. Harmony search (HS) is a recent EA that considers the whole individuals in the breeding step. In this paper, the cellular automata concepts are embedded into the HS algorithm to come up with a new version called cellular harmony search (cHS). In cHS, the population is arranged as a two-dimensional toroidal grid, where each individual in the grid is a cell and only interacts with its neighbors.Thememory consideration and population update aremodified according to cellular EA theory. The experimental results using benchmark functions show that embedding the cellular automata concepts with HS processes directly affects the performance. Finally, a parameter sensitivity analysis of the cHS variation is analyzed and a comparative evaluation shows the success of cHS

Intelligent examination timetabling system using hybrid intelligent water drops algorithm

This paper proposes Hybrid Intelligent Water Drops (HIWD) algorithm to solve Tamhidi programs uncapacitated examination timetabling problem in Universiti Sains Islamic Malaysia (USIM).Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops.The results of this study prove that the proposed algorithm can produce a high quality examination timetable in shorter time in comparison with the manual timetable

Recognizing faces prone to occlusions and common variations using optimal face subgraphs

An intuitive graph optimization face recognition approach called Harmony Search Oriented-EBGM (HSO-EBGM) inspired by the classical Elastic Bunch Graph Matching (EBGM) graphical model is proposed in this contribution. In the proposed HSO-EBGM, a recent evolutionary approach called harmony search optimization is tailored to automatically determine optimal facial landmarks. A novel notion of face subgraphs have been formulated with the aid of these automated landmarks that maximizes the similarity entailed by the subgraphs. For experimental evaluation, two sets of de facto databases (i.e., AR and Face Recognition Grand Challenge (FRGC) ver2.0) are used to validate and analyze the behavior of the proposed HSO-EBGM in terms of number of subgraphs, varying occlusion sizes, face images under controlled/ideal conditions, realistic partial occlusions, expression variations and varying illumination conditions. For a number of experiments, results justify that the HSO-EBGM shows improved recognition performance when compared to recent state-of-the-art face recognition approaches

Adapting And Hybrid Ising Harmony Search With Metaheuristic Components For University Course Timetabling

Masalah Penjadualan Waktu Kursus Universiti (MPWKU) merupakan suatu masalah penjadualan kombinatorik yang rumit. Algoritma Gelintaran Harmoni (AGH) ialah suatu kaedah metaheuristik berdasarkan populasi. Kelebihan utama algoritma ini terletak pada keupayaannya dalam mengintegrasikan komponen-komponen utama bagi kaedah berdasarkan populasi dan kaedah berdasarkan gelintaran setempat dalam satu model pengoptimuman yang sama. Disertasi ini mencadangkan suatu AGH yang telah disesuaikan untuk MPWKU. Penyesuaian ini melibatkan pengubahsuaian terhadap operator AGH. Hasil yang diperoleh adalah dalam lingkungan keputusan terdahulu. Tetapi beberapa kelemahan dalam kadar penumpuan dan eksploitasi setempat telah dikesan dan telah diberikan tumpuan menerusi penghibridan dengan komponen metaheuristik yang diketahui. Tiga versi terhibrid dicadangkan, di mana, setiap hibrid merupakan peningkatan daripada yang sebelumnya: (i) Algoritma Gelintaran Harmoni yang Diubah suai; (ii) Algoritma Gelintaran Harmoni dengan Kadar Penyesuaian Berbagai Nada, dan (iii) Algoritma Gelintaran Harmoni Hibrid. Semua hasil yang diperoleh dibandingkan dengan 21 kaedah lain menggunakan sebelas dataset piawai de facto yang mempunyai saiz dan kekompleksan yang berbeza-beza. University Course Timetabling Problem (UCTP) is a hard combinatorial scheduling prob- !em. Harmony Search Algorithm (HSA) is a recent metaheuristic population-based method. The major thrust of this algorithm I ies in its abiiity to integrate the key components of populationbased methods and local search-based methods in the same optimisation model. This dissertation presents a HSA adapted for UCTP. The adaptation involved modifying the HSA operators. The results were within the range of state of the art. However, some shortcomings in the convergence rate and local exploitation were identified and addressed through hybridisation with known metaheuristic components. Three hybridized versions are proposed which are incremental improvements over the preceding version: (i) Modified Harmony Search Algorithm (MHSA); (ii) Harmony Search Algorithm with Multi-Pitch Adjusting Rate (HSA-MPAR), and (iii) Hybrid Harmony Search Algorithm (HHSA). The results werecompared against 21 other methods using eleven de facto standard dataset of different sizes and complexity

A review of UAV Visual Detection and Tracking Methods

This paper presents a review of techniques used for the detection and tracking of UAVs or drones. There are different techniques that depend on collecting measurements of the position, velocity, and image of the UAV and then using them in detection and tracking. Hybrid detection techniques are also presented. The paper is a quick reference for a wide spectrum of methods that are used in the drone detection process.Comment: 10 page

A harmony search algorithm for university course timetabli

One of the main challenges for university administration is building a timetable for course sessions. This is not just about building a timetable that works, but building one that is as good as possible. In general, course timetabling is the process of assigning given courses to given rooms and timeslots under specific constraints. Harmony search algorithm is a new metaheuristic population-based algorithm, mimicking the musical improvisation process where a group of musicians play the pitches of their musical instruments together seeking a pleasing harmony. The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. In this paper, a harmony search and a modified harmony search algorithm are applied to university course timetabling against standard benchmarks. The results show that the proposed methods are capable of providing viable solutions in comparison to previous works

A harmony search algorithm for nurse rostering problems

Harmony search algorithm (HSA) is a relatively new nature-inspired algorithm. It evolves solutions in the problem search space by mimicking the musical improvisation process in seeking agreeable harmony measured by aesthetic standards. The nurse rostering problem (NRP) is a well-known NP-hard scheduling problem that aims at allocating the required workload to the available staff nurses at healthcare organizations to meet the operational requirements and a range of preferences. This work investigates research issues of the parameter settings in HSA and application of HSA to effectively solve complex NRPs. Due to the well-known fact that most NRPs algorithms are highly problem (or even instance) dependent, the performance of our proposed HSA is evaluated on two sets of very different nurse rostering problems. The first set represents a real world dataset obtained from a large hospital in Malaysia. Experimental results show that our proposed HSA produces better quality rosters for all considered instances than a genetic algorithm (implemented herein). The second is a set of well-known benchmark NRPs which are widely used by researchers in the literature. The proposed HSA obtains good results (and new lower bound for a few instances) when compared to the current state of the art of meta-heuristic algorithms in recent literature

Harmony search hyper-heuristic with different pitch adjustment operator for scheduling problems / Khairul Anwar ... [et al.]

The Harmony Search Algorithm (HSA) has been adapted in the hyper-heuristics framework as the high-level heuristic named Harmony Search-based Hyper Heuristic (HSHH). Two operators in HSA are used to select and generate a heuristics vector. In this paper the pitch adjustment operator was used in order to enhance the original HSHH. The purpose of applying the pitch adjustment operator was to insert a different way of heuristic selection instead of randomness in memory consideration operator. The effectiveness of the proposed methods was tested with two distinct timetabling and rostering problems. Experimentally, the new HSHH method had improved the original HSHH

An ensemble of intelligent water drop algorithm for feature selection optimization problem

Master River Multiple Creeks Intelligent Water Drops (MRMC-IWD) is an ensemble model of the intelligent water drop, whereby a divide-and-conquer strategy is utilized to improve the search process. In this paper, the potential of the MRMC-IWD using real-world optimization problems related to feature selection and classification tasks is assessed. An experimental study on a number of publicly available benchmark data sets and two real-world problems, namely human motion detection and motor fault detection, are conducted. Comparative studies pertaining to the features reduction and classification accuracies using different evaluation techniques (consistency-based, CFS, and FRFS) and classifiers (i.e., C4.5, VQNN, and SVM) are conducted. The results ascertain the effectiveness of the MRMC-IWD in improving the performance of the original IWD algorithm as well as undertaking real-world optimization problems