The muzzle velocity is a key index to reflect the performance of electromagnetic(EM) railgun. In order to obtain an optimal solution of muzzle velocity accurately and quickly in numerical simulation, an approach of co...
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ISBN:
(纸本)9781479927333
The muzzle velocity is a key index to reflect the performance of electromagnetic(EM) railgun. In order to obtain an optimal solution of muzzle velocity accurately and quickly in numerical simulation, an approach of combining orthogonal design method(ODM) and harmonysearch(HS) algorithm is presented. There are up to 11 factors to be considered in affecting the muzzle velocity, including eight trigger delay times of pulsed power supply (PPS), the operating voltage of PPS, the length of rail and the mass of projectile. By ODM analysis, the best level combinations of these factors are selected and the significant degree of these factors is ordered. Therefore, the varying ranges of these factors are decided and a hierarchical factor optimization model is built. The optimization model is solved by HS algorithm with the penalty function method added to satisfy process constraints, such as the peak of current is bounded under 420KA. Finally, the proposed approach and the simple HS algorithm are compared. The results indicate that, by using the proposed approach, the average of original velocity is increased by 43.53%, and the average of best velocity at last, is increased by 1.34%
In the paper a description of procedure for solving the inverse problem of continuous casting is given. The problem consists in reconstruction of the cooling conditions of solidified ingot and is based on minimization...
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ISBN:
(纸本)9783642552243
In the paper a description of procedure for solving the inverse problem of continuous casting is given. The problem consists in reconstruction of the cooling conditions of solidified ingot and is based on minimization of the appropriate functional by using the modified harmony search algorithm - the algorithm of artificial intelligence inspired by process of composing the jazz music.
This paper addresses a new optimization method for a variant of the category of orienteering problems (OP), which is well-known as the capacitated team orienteering problem (CTOP). The main objective of CTOP focuses o...
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ISBN:
(数字)9783030386290
ISBN:
(纸本)9783030386290;9783030386283
This paper addresses a new optimization method for a variant of the category of orienteering problems (OP), which is well-known as the capacitated team orienteering problem (CTOP). The main objective of CTOP focuses on the maximization of the total collected profit from a set of candidate nodes or customers by taking into account the limitations of vehicle capacity and time upper boundary of a constructed route. To solve CTOP, we present a new optimization algorithm called the Similarity Hybrid harmonysearch. This methodology includes an innovative "similarity process" technique, which takes advantage the most profitable nodes/customers during the algorithmic procedure aiming to extend the diversification in the solution area. The experimental tests were conducted in the most popular set of instances and the obtained results are compared with most competitive algorithms in the literature.
harmonysearch (HS) algorithm, applied in many fields, is a new population algorithm, which imitates magically the phenomenon of musical improvisation process. However, it has a potential shortage, which is easily tra...
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ISBN:
(纸本)9781538612446
harmonysearch (HS) algorithm, applied in many fields, is a new population algorithm, which imitates magically the phenomenon of musical improvisation process. However, it has a potential shortage, which is easily trapped into local optima when searching for global optima. To solve this problem, a hybrid harmony search algorithm (HHS) is promoted, which is based on the conception of swarm intelligence HHS employed a local search method to replace the pitch adjusting operation, and designed an elitist preservation strategy to modify the selection operation. Expeliment results demonstrated that the proposed method performs much better than the HS and its improved algorithms (IHS, GHS and NGIIS).
harmony search algorithm is a meta-heuristic, nature-inspired optimization algorithm that tries to mimic real-life improvisations that musicians use to generate a harmony that is more pleasing to hear. This paper pres...
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ISBN:
(纸本)9789811965814;9789811965807
harmony search algorithm is a meta-heuristic, nature-inspired optimization algorithm that tries to mimic real-life improvisations that musicians use to generate a harmony that is more pleasing to hear. This paper presents and compares three different types of harmony search algorithms. We start with the implementation of the original HSA. Further, two different modifications were made to the original HSA, the first one uses fitness proportionate selection of harmonies from the HM and is known as biased Roulette harmony search algorithm (BRHSA) and the second one builds on BRHSA by adding simple mathematics to further guide the algorithm toward the desired solution and is called guided biased Roulette harmony search algorithm (GBRHSA). These three variants of HSA were applied on four benchmark test functions on the same machine, and the results obtained after 30 runs were noted down for comparison. It was observed that the results given by the three variants had no specific trend in terms of best result or computational time and the performance of a particular variant was subject to parameters like the kind of function and its search domain. The results presented in this paper can be used as a foundation for the future works that will be done on this algorithm and can help derive an apt variant of HSA for solving a particular problem.
This paper proposes a novel discrete harmonysearch (DHS) algorithm to minimize makespan for a lot-streaming flow shop scheduling problem with sequence dependent setup times. Unlike the traditional harmonysearch (HS)...
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ISBN:
(纸本)9781424451821
This paper proposes a novel discrete harmonysearch (DHS) algorithm to minimize makespan for a lot-streaming flow shop scheduling problem with sequence dependent setup times. Unlike the traditional harmonysearch (HS) algorithm, the proposed OHS algorithm utilizes job permutations to represent harmonies and applies a job-permutation-based improvisation to generate new harmonies. To enhance the algorithm's searching ability, an effective initialization scheme based on the NEH heuristic is developed to construct an initial harmony memory with certain quality and diversity, and an efficient local searchalgorithm based on the insert neighborhood structures is fused to stress the local exploitation. Extensive computational simulations and comparisons are provided, which demonstrate the effectiveness of the proposed DHS against the best performing algorithms from the literature.
Evolutionary algorithms (EA) are robust optimization approaches which have been successfully applied to a wide range of problems. However, these well-established metaheuristic strategies are computationally expensive ...
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Evolutionary algorithms (EA) are robust optimization approaches which have been successfully applied to a wide range of problems. However, these well-established metaheuristic strategies are computationally expensive because of their slow convergence rate. Opposition Based Learning (OBL) theory has managed to alleviate this problem to some extent. Through simultaneous consideration of estimates and counter estimates of a candidate solution within a definite search space, better approximation of the candidate solution can be achieved. Although it addresses the slow convergence rate to some extent, it is far from alleviating it completely. The present work proposes a novel approach towards improving the performance of OBL theory by allowing the exploration of a larger search space when computing the candidate solution. Instead of considering all the components of the candidate solution simultaneously, the proposed method considers each of component individually and attempts to find the best possible combination by using a metaheuristic technique. In the present work, this improved Opposition learning theory has been integrated with the classical HS algorithm, to accelerate its convergence rate. A comparative analysis of the proposed method against classical Opposition Based Learning has been performed on a comprehensive set of benchmark functions to prove its superior performance.
Path planning represents an important optimization problem that need to be solved in various applications. It is a hard optimization problem thus deterministic algorithms are not usable but it can be tackled by stocha...
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ISBN:
(纸本)9783030319670;9783030319663
Path planning represents an important optimization problem that need to be solved in various applications. It is a hard optimization problem thus deterministic algorithms are not usable but it can be tackled by stochastic population based metaheuristics such as swarm intelligence algorithms. In this paper we adopted and adjusted harmony search algorithm for the path planning problem in environment with static obstacles and danger zones. Objective function includes path length and safety degree. The proposed method was tested on standard benchmark examples from literature. Simulation results show that our proposed model produces better and more consistent results in spite of its simplicity.
In the last four decades, many studies have been conducted for least-cost and maximum-reliability design of water supply systems. Most models employed multi-objective genetic algorithm (e.g., non-dominated sorting gen...
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ISBN:
(纸本)9783662479261;9783662479254
In the last four decades, many studies have been conducted for least-cost and maximum-reliability design of water supply systems. Most models employed multi-objective genetic algorithm (e.g., non-dominated sorting genetic algorithm-II, NSGA-II) in order to explore trade-off relationship between the two objectives. This study proposes a reliability-based design model that minimizes total cost and maximizes seismic reliability. Here, seismic reliability is defined as the ratio of available demand to required water demand under earthquakes. Multi-objective harmony search algorithm (MoHSA) is developed to efficiently search for the Pareto optimal solutions in the two objectives solution space and incorporated in the proposed reliability-based design model. The developed model is applied to a well-known benchmark network and the results are analyzed.
The increasing amount of text information on the Internet web pages affects the clustering analysis. The text clustering is a favorable analysis technique used for partitioning a massive amount of information into clu...
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ISBN:
(纸本)9781467389136
The increasing amount of text information on the Internet web pages affects the clustering analysis. The text clustering is a favorable analysis technique used for partitioning a massive amount of information into clusters. Hence, the major problem that affects the text clustering technique is the presence uninformative and sparse features in text documents. The feature selection (FS) is an important unsupervised technique used to eliminate uninformative features to encourage the text clustering technique. Recently, the meta-heuristic algorithms are successfully applied to solve several optimization problems. In this paper, we proposed the harmonysearch (HS) algorithm to solve the feature selection problem (FSHSTC). The proposed method is used to enhance the text clustering (TC) technique by obtaining a new subset of informative or useful features. Experiments were applied using four benchmark text datasets. The results show that the proposed FSHSTC is improved the performance of the k-mean clustering algorithm measured by F-measure and Accuracy.
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