Bat-inspired Optimization Algorithm Research Papers

The Unified Quantum-Consciousness Framework Integrating EQST-GP Physics with Veronica X Pro Architecture for Conscious AI

by Prof Ahmed Ali

2025, The Unified Quantum-Consciousness Framework Integrating EQST-GP Physics with Veronica X Pro Architecture for Conscious AI

This paper presents a comprehensive unification of the Expanded Quantum String Theory with Gluonic Plasma (EQST-GP) framework with the Veronica X Pro quantum-neural architecture, creating a complete theoretical and computational paradigm... more

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A Comparative Study on Multi-Swarm Optimisation and Bat Algorithm for Unconstrained Non Linear Optimisation Problems

by Stephen O Oppong

2025, DOAJ (DOAJ: Directory of Open Access Journals)

A study branch that mocks-up a population of network of swarms or agents with the ability to self-organise is Swarm intelligence. In spite of the huge amount of work that has been done in this area in both theoretically and empirically... more

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SOCIAL MEDIA INFLUENCE MAXIMIZATION USING LOGISTIC REGRESSION MACHINE LEARNING ALGORITHM

by Uma Maheswari P

2025, INTERNATIONAL CONFERENCE ON RECENT TRENDS IN COMPUTATIONAL TECHNOLOGIES AND SUSTAINABLE DEVELOPMENT GOALS

Users' interactions with content and with one other in social networks are greatly influenced by social homophily and influence in social recommendation systems. This plays a crucial part in deciding how consumers engage with the... more

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UMA PSG NCSCD 2024

by Uma Maheswari P

2025, Proceedings of Second National Conference on Sustainable Computing and Development (NCSCD) – 2024 supported by PSGCARE on 02-02-2024, ISBN NO: 978-93-95105-59-0

Social Homophily and Influence Predictive modeling for Social Recommendation is a vital tool in various fields, aiding in decision-making and forecasting future trends. This research delves into an innovative approach that combines... more

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Design Optimization of Semi-Rigidly Connected Steel Frames Using Harmony Search Algorithm

by Mohammed Arafa

2025, Journal of Engineering Research and Technology

In this paper, a design optimization algorithm is presented for non-linear steel frames with semi-rigid beamcolumnconnections using harmony search algorithm. The design algorithm obtains the minimum steel weight by selecting from a... more

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A prosperous and thorough analysis of gravity profiles for resources exploration utilizing the metaheuristic Bat Algorithm

by Omar A . Gomaa

2025

Here, we present a remarkable methodology for unveiling subsurface structures with the potential to transform the exploration of mineral and ores resources, as well as the study of volcanic activity. By incorporating the Metaheuristic Bat... more

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BIASED CLUSTERING AND FEATURE SELECTION FOR ENHANCED PREDICTIVE MODELING IN SOCIAL MEDIA INFLUENCE MAXIMIZATION

by Uma Maheswari P

2025, JOURNAL OF RESEARCH ADMINISTRATION

Social Homophily and Influence Predictive modeling for Social Recommendation is a vital tool in various fields, aiding in decision-making and forecasting future trends. This research delves into an innovative approach that combines... more

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INFLUENCE MAXIMIZATION IN SOCIAL MEDIA WITH BIASED RENOVATE K-MEAN CLUSTERING AND BIASED BAT ALGORITHM

by Uma Maheswari P

2025, AFRICAN JOURNAL OF BIOLOGICAL SCIENCES

Social media has become an indispensable part of our everyday lives in the current digital age. These digital platforms are essential for information sharing, communication, and building meaningful relationships. Information... more

Social media has become an indispensable part of our everyday lives in the
current digital age. These digital platforms are essential for information sharing,
communication, and building meaningful relationships. Information dissemination in these
social networks has become a major concern for many industries, including marketing,
banking, politics, research, and education. Various models have been used to illustrate the
dynamics of information sharing in these kinds of networks. Still, the concept of influence is
extremely important for people and companies alike. Because influence maximization has
the ability to reach and effect a large audience, it has received a lot of attention, especially in
the context of social networks. This complex issue is sometimes described as the "influence
maximization problem," This research presents a novel method to improve influence
maximization by utilizing the Biased Bat Algorithm. Maximizing influence is a crucial
problem in network analysis, which is frequently done in social networks. Influence can be
compared to a cascade effect, in which a small number of people's activities set off a series of
events that eventually affect a big chunk of the network. Finding these "influencers" is
essential for effective resource distribution and knowledge sharing. Selecting the best vertex
in the graph out of all the vertices is one of the key steps in determining the highest
influence. This research presents a new method to find the maximum influence in social
networks based on the Biased Bat algorithm. The proposed method aims to find the
maximum influence in the social network graph that has a good fitness degree. The algorithm
can identify potential influencers. Our simulations across multiple networks have
unequivocally showcased the superiority of this algorithm as the preeminent and scalable
solution to the influence maximization problem. The experimental outcomes clearly
delineate that the employment of the MFA (Maximal First Activation) approach effectively
diminishes the execution time required to approximate the maximum influence.

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Improving an Industrial problem optimizing the material in car seats

by Alberto Ochoa Zezzatti

2024, Int. J. Comb. Optim. Probl. Informatics

Resumen en: In the present study explainsthe design of an intelligent systembased on bio-inspired algorithm as an aid in the strategic planning to improve the dismin...

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Design Optimization of semi rigid steel framed Structures to AISC-LRFD using Harmony search algorithm

by Mohammed Arafa

2024

The aim of this research is to develop a computer design model which obtains the optimum design of multistorey steel frames by selecting from a standard set of steel sections. Strength constraints of American Institute Steel Construction... more

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Enhanced KGCS for Engineering Design

by Adina V. Crișan

2024

This paper presents an optimization algorithm called KGCS suitable to be used for different engineering problems. The efficiency of the algorithm is given by the aggregation between the particularities of the Cuckoo Search algorithm and... more

Fig. 1. A 2D Lévy flight of 500 steps with (0,0) as starting point [8].

Pc is the beam bucking load and x,,x, 20.

Fig. 5. A schematic view of the speed reducer This second engineering design benchmark problem consists in minimizing the weight of the speed reducer while respecting the constraints on bending stress of the gear teeth, surface stress, transverse deflections of the shafts and stresses in the shaft. The problem is formulated as follows:

less than 20000 objective function evaluations

of the second shaft (x,). A schematic view of

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Bat Algorithm Implementation on Economic Dispatch Optimization Problem

by Rashed Marimi

2024

Power plant is one of the substantial industry in a country since it supports various needs of people. Optimum cost for running this industry is a necessity so that power generated can be produce according to power demand with appropriate... more

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A new modification approach on bat algorithm for solving optimization problems

by ecir uğur küçüksille

2024, Applied Soft Computing

Optimization can be defined as an effort of generating solutions to a problem under bounded circumstances. Optimization methods have arisen from a desire to utilize existing resources in the best possible way. An important class of... more

Table 11: The comparative results of EBA and existing improvement approaches In this test stage, it has been planned to investigate the performance of EBA on constrained engineering problems. For this purpose, three well known real world problems have been chosen from the literature [24, 25]. They are, welded beam design, spring design and pressure vessel de- sign. The results obtained from these problems have been compared with the studies (in particular, published after 2007) in the literature. For fair comparison, the efficiency of each approach has been measured by comparing function evaluation number (FEN), which is equal to the population size multiplied by the number of iterations proceeded. For constrained problems, N has been set to 20, 10 and 25; maximum number of iterations has been set to 2000, 500 and 600 for these problems respectively, R has been taken as 30.

where X;, SD, and n; are mean, standard deviation and size of the first sample (BA or GA), while X>, SD and n2 are mean, standard deviation and size of the second sample (EBA) respec- tively. ¢ value can be positive or negative. Positive and negative values mean that EBA and BA (or GA) have produced better solutions during optimization process respectively. In this study, the confidence interval has been set at the 95% which means fg 95=1.96. When t>1.96, the difference between two samples is significant and EBA is better than BA (or GA); on the other hand when t<-1.96, BA (or GA) is better than EBA. The rightmost 4 columns of Tables 9-10 indicate which algorithm has provided the better solution.

Figure 10: Graphical comparison of BA and EBA in terms of best, worst, mean values.

Table 6: Mean normalized values of Cini: on numerical functions ¥y Table 7: Optimum parameter values obtained after training

Table 1: The unconstrained functions used for analyzing results have been normalized and shown in Table 2. As it is seen from the results, the algorithm can produce better solutions as loudness value increases with some exceptions. When A is 0.9 or 1, algorithm produces better cost value when compared with other values, that’s why A has been set as 0.95.

As seen in Fig. 13, a cylindrical pressure vessel is capped at both ends by hemispherical heads. The objective of this problem is to minimize the cost value including welding, material and forming costs. Pressure vessel problem has four design variables (x1, x2, x3 and x4) and four constraints. The thickness is T; (x;), thickness of the head is 7), (x2), inner radius is R (x3) and the length of the cylindrical section of the vessel is L (x4). The variables x; and x2 are discrete and integer multiples of 0.0625 inch. Boundaries of these parameters are 1x0.0625 < x1,x2 < 99x0.0625 and

Table 4: Mean normalized values of fingx on numerical functions

Table 2: Mean normalized values of A on numerical functions

Table 8: Performance of modification structures on bat algorithm

it would not be wrong to say that EBA have actually produced the same values as GA did on the 8th function. On the other hand, when CR values, ranging from 0.44 to 0.99, are considered, it is understood that EBA can converge to the point where BA reaches at the end of iterations faster than BA.

1 . not available. @ ATS: Artificial Immune System, ? Bacterial Foraging Algorithm, ° Differential Evolution, 4 NM:Nelder-Mead, ° Evolutionary Algorithm, / T-Cell Algorithm, Charged System Search, ” ID: Integer-discrete, ‘ Firefly Algorithm, / Mine Blast Algorithm, * Hybrid Taguchi-Differential Evolution, ! Interior Search Algorithm,

where Snax and Sj in are the maximum and the minimum number of seeds to be producec respectively, Uyors¢ aNd Upes; Indicate the worst and the best fitness values respectively whil u; indicates the fitness value of the ith solution.

OO > Ty Aa - a ie -—— ae FE EEE er SE EE BN em ES ENE OE IIL SELES da ESE SES refer to [25]. The results have been given in Table 12. The results in Table 12 point out that all studies has achieved acceptable solutions without exceeding the boundaries. The studies [71, 74, 77] seem to find best cost value, however; they neglected the discrete variables and regarded them as continuous. EBA has found the compelling cost value within minimum FEN without abandoning any rules of the problem.

Even though pressure vessel is relatively harder to solve than the problems with continuous variables, EBA can find the minimum value of this problem together with [46], [81] and [24] as seen in Table 14. When the “mean” values in the table are considered, it is noticed that EBA is better than all of the studies except [78]. However, to find such an objective value He and Wang needed much more than ten times FEN that EBA has needed. Note that only the studies producing feasible solutions have been regarded for evaluation.

Figure 6: The distance of seeds to their parent during 500 iterations.

method has accomplished to find the minimum cost value without violating the boundaries of the problem.

towards the end of optimization process, the ith solution can have no chance to get away from that undesired local minimum as the movement of the ith particle depends on such best solution towards the end of the optimization process. This modification has been described in detail by Fig. 3. Figure 3: Distribution of the population towards the end of the iteration on Schwefel function

We lable ICPlesent UNIMOG! alla MIUINOGal LUNCUONS TCSpCCUVCLY, The parameters of population number (NV), dimension of a function (d), function evaluation number (FEN) and run time (R) have been set as 50, 10, 2x10° and 20 respectively. Only the average of cost values obtained at the end of each runtime has been considered in the comparison phase. The optimum parameter values used for experiments in this study have been summarized in Table 7.

Pseudo-code and flow chart of the algorithm are given in algorithm | and Fig. 2 respectivel:

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Modified Bat Algorithm

by ecir uğur küçüksille

2024, Electronics and Electrical Engineering

Heuristic optimization algorithms which are inspired by nature have become very popular for solving real world problems recently. The use of these algorithms increases day by day in the literature because of their flexible structures and... more

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A note on the conjecture of the autotopism group of the Figueroa’s presemifields

by Walter Melendez

2024, Selecciones matematicas

A note on the conjecture of the autotopism group of the Figueroa's presemifields Una nota sobre la conjetura del grupo de autotopismos de los presemicuerpos de Figueroa

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A note on the conjecture of the autotopism group of the Figueroa’s presemifields

by Walter Melendez

2024, Selecciones Matemáticas

A note on the conjecture of the autotopism group of the Figueroa's presemifields Una nota sobre la conjetura del grupo de autotopismos de los presemicuerpos de Figueroa

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Bat Algorithm

by lagouge TARTIBU

2024, Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

Bat Algorithm 8.1 Introduction Bat algorithm is an innovative or population-based technique which belongs to the swarm intelligence. It is also referred to as a metaheuristic algorithm developed by Yang [1]. The bat algorithm as a unique... more

Bat Algorithm 8.1 Introduction Bat algorithm is an innovative or population-based technique which belongs to the swarm intelligence. It is also referred to as a metaheuristic algorithm developed by Yang [1]. The bat algorithm as a unique algorithm provides a suitable solution technique than numerous and prevalent classical and heuristic algorithms. The algorithm is used for quick decision making and for solving complex problems in diverse fields of operations ranging from engineering, business, transportation, and other fields of human endeavor. It is important to understand the communication and navigational pattern of bats while defining the algorithm since the algorithm is based on the micro-bats echolocation (EL) [1]. EL is an enchanting and captivating sonar propensity produced bats. The appealing wave of sound made by the bats is a great strength they often exhibit while searching for prey. The wave of sound is a formula they adopt not only in food search but serves other purposes [2]. For instance, while searching for food in a completely dark environment, there might be obstacles or dangers on their way to the food source. This can easily be detected in some magical manner as they can sense and discern possible danger on their way to the food source as shown in Fig. 8.1 [3]. The structure and flying position of a bat is shown in Fig. 8.1. BA is therefore a very powerful algorithm as it uses the frequency-tuning methodology for range intensification of the solutions in the population. At the same time, the BA system implements the instinctive skyrocketing or zooming procedure to maintain stability during the food search or exploration process. In developing the BA, the pattern of direction finding, manipulation, and exploration during prey hunting is taken into consideration by mimicking the disparities in terms of emission rates of pulse and intensity of sound released by the bats while hunting or searching for prey. The algorithm demonstrates a high level of efficiency with a distinctive swift start process (Fig. 8.2).

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Performance of surrogate models in reliability-based design optimization

by Santiago hernandez

2024, High Performance and Optimum Design of Structures and Materials

Structural designs are progressively more conditioned by uncertainty in a wide range of fields, and new designs have to meet the requirements of safety and efficiency. Probabilistic optimization is a powerful tool able to improve and... more

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Artificial rat optimization with decision-making: A bio-inspired metaheuristic algorithm for solving the traveling salesman problem

by toufik mzili

2024, Decision Making: Applications in Management and Engineering

In this paper, we present the Rat Swarm Optimization with Decision Making (HDRSO), a hybrid metaheuristic algorithm inspired by the hunting behavior of rats, for solving the Traveling Salesman Problem (TSP). The TSP is a well-known... more

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Layout Optimization of Braced Frames Using Differential Evolution Algorithm and Dolphin Echolocation Optimization

by Neda Far

2024, Periodica Polytechnica-civil Engineering

In this study, topology optimization is applied to concentrically braced frames in order to find economical solutions for conventional structural steel frames. Differential Evolution Algorithm and Dolphin Echolocation Optimization are... more

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Layout Optimization of Braced Frames Using Differential Evolution Algorithm and Dolphin Echolocation Optimization

by Neda Far

2024, Periodica Polytechnica Civil Engineering

In this study, topology optimization is applied to concentrically braced frames in order to find economical solutions for conventional structural steel frames. Differential Evolution Algorithm and Dolphin Echolocation Optimization are... more

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Solving patient referral problems by using bat algorithm

by Ping-Shun Chen

2024, Technology and Health Care

BACKGROUND: A two-hospital patient referral problem intends to calculate an optimal value of referral patients between two hospitals and to evaluate whether or not the current number of referral patients is too low. OBJECTIVE: The goal of... more

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Reliability Analysis of Structures Using Modified FA_PSO Algorithm

by majid taheri

2023

Designing buildings with a very high safety factor is one of the main purposes of a civil engineer. Since in the structural design process, there are several no-confidence; we cannot achieve a perfect safe design. In these cases, we face... more

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A Discrete Bat Algorithm for the Examination Timetabling Problem

by Egbert Mujuni

2023, DergiPark (Istanbul University)

Bat Algorithm (BA) is one of the newest and promising nature inspired metaheuristics. Introduced by Yang in 2010, BA is a population method which is based on the echolocation characteristics of microbats. The original BA was proposed only... more

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Artificial rat optimization with decision-making: A bio-inspired metaheuristic algorithm for solving the traveling salesman problem

by Mohammed Essaid Riffi

2023, Decision Making: Applications in Management and Engineering

In this paper, we present the Rat Swarm Optimization with Decision Making (HDRSO), a hybrid metaheuristic algorithm inspired by the hunting behavior of rats, for solving the Traveling Salesman Problem (TSP). The TSP is a well-known... more

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Artificial rat optimization with decision-making: A bio-inspired metaheuristic algorithm for solving the traveling salesman problem

by ilyass mzili

2023, Decision Making

In this paper, we present the Rat Swarm Optimization with Decision Making (HDRSO), a hybrid metaheuristic algorithm inspired by the hunting behavior of rats, for solving the Traveling Salesman Problem (TSP). The TSP is a well-known... more

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Artificial rat optimization with decision-making: A bio-inspired metaheuristic algorithm for solving the traveling salesman problem

by ilyass mzili

2023, Decision Making: Applications in Management and Engineering

In this paper, we present the Rat Swarm Optimization with Decision Making (HDRSO), a hybrid metaheuristic algorithm inspired by the hunting behavior of rats, for solving the Traveling Salesman Problem (TSP). The TSP is a well-known... more

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Image Fusion Algorithm using Grey Wolf optimization with Shuffled Frog Leaping Algorithm

by Waleed Mahmoud

2023, International Journal of Innovative Computing

Data fusion is a “formal framework in which are expressed the means and tools for the alliance of data originating from different sources.” It aims at obtaining information of greater quality; the exact definition of 'greater quality... more

Fig .1. Hierarchy of grey wolf (dominance decrease from top down) In the GWO algorithm, the social hierarchy as well as the hunting technique of these wolves are simulated and modelled mathematically. In the next section we will discuss the hunting technique and the mathematical models [12], [13].

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Eurasian oystercatcher optimiser: New meta-heuristic algorithm

by Mohammed Al-Yousif

2023, Journal of Intelligent Systems

Modern optimisation is increasingly relying on meta-heuristic methods. This study presents a new meta-heuristic optimisation algorithm called Eurasian oystercatcher optimiser (EOO). The EOO algorithm mimics food behaviour of Eurasian... more

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Applications of the anarchic society optimization (ASO) algorithm for optimizing operations of single and continuous multi-reservoir systems

by Milad Latifi

2023, Journal of Water Supply: Research and Technology - Aqua

To address water resources-related management issues, different evolutionary and heuristic algorithms have been developed in recent years. In this paper, a new algorithm is introduced for optimizing the operation of reservoir systems.... more

Figure 6 | Best and worst convergence of ASO for (a) Ackley, (c) Styblinski-Tang, and (e) Holder table functions; and average convergence of ASO and GA for (b) Ackley, (d) Styblinski-Tang and (f) Holder table functions. global optima for all three test functions. Also, the ASO two test functions of Styblinski-Tang and Holder table algorithm resulted in better average and worst answers in the 10 consequent runs than the GA method. For the two test functions of Styblinski-Tang and Holder table, are 7.83 x 10°, —78.33 and —19.21, respectively. As shown in a Table 2, the ASO algerthin restilts are cleser to the

Figure 12 | Temporal variations in storage volume of the four-reservoir system optimized by the ASO algorithm and GA.

Figure 9 | Variations of optimal storage volumes of Karun-4 reservoir during the operation period. Figure 7(b) shows the convergence of the best and worst solutions of the ASO algorithm; Figure 7(d) presents the solutions of the ASO algorithm; Figure 7(d) presents the

Figure 7 | Minimum (best) and maximum (worst) rates of convergence of the ASO algorithm over 10 runs for (a) Karun-4 reservoir and (b) four-reservoir system; and average rates of convergence of the GA and ASO methods from 10 runs for (c) Karun-4 reservoir and (d) four-reservoir system.

Figure 10 | Optimal power generation during the Karun-4 operation period.

Figure 4 | Area-volume-elevation curves for Karun-4 reservoir. The minimum and maximum volumes of the reservoir are 1.141x 10° and 190x10° m®, respectively. The power plant capacity (PPC) is equal to 1.0 x 10° W. Optimization of the Karun-4 reservoir operation was performed by using the ASO algorithm and GA on monthly time steps for a five-year period. The amount of generated power is calcu- lated by: The minimum and maximum volumes of the reservoir

Table 3 | Parameters of the ASO algorithm and GA used for the reservoir system problems algorithm yielded very stable results. The coefficient of vari-

Figure 5 | Schematic of the four-reservoir system.

Table 1 | Characteristics of ASO algorithm and GA used for three benchmark functions Results for three mathematical functions GA and the ASO algorithm for the three benchmark func- tions are shown in Table 2.

Figure 8 | Optimal releases of Karun-4 reservoir during the operation period.

Figure 11 | Monthly releases of the four-reservoir system optimized by the ASO algorithm and GA.

Table 2 | Values of objective function calculated with ASO algorithm and GA from 10 different runs for three benchmark functions

Figure 2 | Flowchart of different steps of research. ELIO TMAUICIIALCaL LULICUIOTIS UsOU Lil Ulls UUTILOCAL ale Ackley, Styblinski-Tang, and Holder table, which are described by Equations (9)-(11), respectively.

Figure 3 | Mathematical test functions: (a) Ackley; (b) Styblinski-Tang; (c) Holder table.

able 4 | Statistical outputs from 10 runs of the ASO algorithm and GA for the reservoir system problems

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A hybrid algorithm to bypass some weak features in the particle swarm and firefly algorithms...with an application to the traveling salesman problem

by muna shaker salman

2023, Tikrit Journal of Administrative and Economic Sciences

In this paper, the Traveling Salesman Problem (TSP) is solved through the use of some approximation techniques where the results of the previous work showed some defects in solving the problem to obtain an optimal or close to optimal... more

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Solid Waste Collection Routing Optimization using Hybridized Modified Discrete Firefly Algorithm and Simulated Annealing - A Case Study in Davao City, Philippines

by Cinmayii Manliguez

2023, Proceedings of the 3rd International Conference on Geographical Information Systems Theory, Applications and Management

Modified Discrete Firefly-Simulated Annealing (MDF-SA) Algorithm was used to solve travelling salesman problem (TSP) using the tanh function for discretization. MDF-SA was tested on four (4) data instances from TSPLIB and the Davao City... more

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A novel meta-heuristic based on soccer concepts to solve routing problems

by Fernando Diaz

2023, GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference Companion

In this paper, we describe a new meta-heuristic to solve routing problems. This meta-heuristic is called Golden Ball (GB), and it is based on soccer concepts. To prove its quality we apply it to the Vehicle Routing Problem with Backhauls... more

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Guided stochastic search technique for discrete sizing optimization of steel trusses: A design-driven heuristic approach

by Mehmet Polat Saka

2023, Computers & Structures

This study presents a design-driven heuristic approach named guided stochastic search (GSS) technique for discrete sizing optimization of steel trusses. The method works on the basis of guiding the optimization process using the... more

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Development of a Novel Hybrid Optimization Algorithm for Minimizing Irrigation Deficiencies

by HUZAIFA HASHIM

2023, Sustainability

One of the most important issues in the field of water resource management is the optimal utilization of dam reservoirs. In the current study, the optimal utilization of the Aydoghmoush Dam Reservoir is examined based on a hybrid of the... more

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Prediction of the effect of varying cure conditions and w/c ratio on the compressive strength of concrete using artificial neural networks

by Hasbi YAPRAK

2023, Neural Computing and Applications

The present study aims at developing an artificial neural network (ANN) to predict the compressive strength of concrete. A data set containing a total of 72 concrete samples was used in the study. The following constituted the concrete... more

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Electrostatic Discharge Algorithm for Optimum Design of Real-Size Truss Structures

by Tevfik O Örmecioğlu

2023, Springer Tracts in Nature-Inspired Computing

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Micro Bat Algorithm for High Dimensional Optimization Problems

by OSMAN TOPAL

2023, International Journal of Computer Applications

Very recently bat inspired algorithms have gained increasing attention as a powerful technique for solving optimization problems. Bat algorithm (BA) is the first one in this group. It is based on the echolocation behavior of bats. BA is... more

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Framework for Bat Algorithm Optimization Metaheuristic

by Adis Alihodzic

2023

This paper describes an object-oriented software system for continuous optimization by a new metaheuristic method, the Bat Algorithm, based on the echolocation behavior of bats. Bat algorithm was successfully used for many optimization... more

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Improved Hybridized Bat Algorithm for Global Numerical Optimization

by Adis Alihodzic

2023, 2014 UKSim-AMSS 16th International Conference on Computer Modelling and Simulation

Swarm intelligence algorithms have been successfully applied to intractable optimization problems. Bat algorithm is one of the latest optimization metaheuristics and research about its capabilities and possible improvements is at the... more

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Some applications of reliability based design optimization in engineering structures

by Santiago Hernández

2023

Structures are subject to uncertainty parameters that need to be considered in the design process. Reliability Based Design Optimization (RBDO) has become a powerful tool in achieving the optimum design when considering uncertainty data.... more

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An Improved Chaotic Bat Algorithm for Solving Integer Programming Problems

by Osama Abdelraouf

2023, International Journal of Modern Education and Computer Science

Bat Algorithm is a recently-developed method in the field of computational intelligence. In this paper is presented an improved version of a Bat Meta-heuristic Algorithm, (IBACH), for solving integer programming problems. The proposed... more

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Bat algorithm for dam–reservoir operation

by Sayed-farhad Mousavi

2023, Environmental Earth Sciences

Optimizing reservoir operation rule is considered as a complex engineering problem which requires an efficient algorithm to solve. During the past decade, several optimization algorithms have been applied to solve complex engineering... more

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The Harmony Search algorithm with additional improvement of harmony memory for Asymmetric Traveling Salesman Problem

by Urszula Boryczka

2023, Expert Systems with Applications

This article constitutes the continuation of the work on adapting the Harmony Search algorithm to effectively solve the Asymmetric Traveling Salesman Problem (ATSP) instances. The author's modification suggested in this work enables the... more

Detailed results for HSIHM3 with MOD = 0.5.

Place of HS among the selected metaheuristic algorithms based on Manjarres et al. (2013). Table 1

Fig. 7. Harmony Search pseudocode with the harmony memory improvement for ATSP. On the basis of Boryczka and Szwarc (2018a), it was assumed that the following values of parameters describing HSIHM will be used: R = 1000, HMS = 5, HMCR = 0.98, and PAR = 0.25. Addition- ally, on the basis of the analysis of the number of iterations after which the algorithm achieved convergence for the examined tasks (presented by Boryczka & Szwarc, 2018b), it was established that IT = 1,000,000. The effectiveness of the approach under analysis was verified on the basis of 19 instances of the ATSP (their characteristics were presented in Table 3). Each benchmark test was solved 30 times.

Fig. 1. Division of the metaheuristic algorithms based on Manjarres et al. (2013).

Comparison of the obtained results with the results presented in reference articles.

Fig. 8. Comparative study of the average error and MOD values.

Fig. 3. Block diagram of the Harmony Search.

The characteristics of tasks used in the study based on Osaba, Diaz, Onieva et al. (2014). Table 3

Comparison of the average error achieved by HSIHM3 with different values of MOD.

Fig. 2. Visualization of the three-stage improvisation. that jazz musicians during improvised music sessions make intu- itive choices regarding the appropriate melodic lines to achieve the best possible sound while playing a piece of music. The al- gorithm assumes the occurrence of harmony memory (HM) storing harmony memory size (HMS) randomly generated solutions (har- monies) having n real coordinates (referred to as pitches). The HM is usually modeled as a matrix having HMS rows and n columns, which was presented in formula (1).

Fig. 5. Harmony Search pseudocode for ATSP (Boryczka & Szwarc, 2018). Table 2 The parameters of the laptop used to conduct the study.

Fig. 4. An exemplary instance of the Traveling Salesman Problem.

itations, referred to as Miller, Tucker and Zemlin (MTZ):

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An enhanced simulation-based design method coupled with meta-heuristic search algorithm for accurate reliability-based design optimization

by Naser safaeian hamzehkolaei

2023, Engineering with Computers

Find d = (d 1 , d 2 ,. .. , d D) Minimize cost = f (X, d) Subject to Pr[G i (X, d) ≤ 0] ≤ PF * i , i = 1, 2,. .. , M, and side constraints d L ≤ d ≤ d U Abstract The enhanced weighted simulation-based design method in conjunction with... more

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Bat-inspired Optimization Algorithm

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